LM Format Enforcer Regular Expression Generation¶
Generate structured data with lm-format-enforcer via LlamaIndex.
With lm-format-enforcer, you can guarantee the output structure is correct by forcing the LLM to output desired tokens.
This is especialy helpful when you are using lower-capacity model (e.g. the current open source models), which otherwise would struggle to generate valid output that fits the desired output schema.
lm-format-enforcer supports regular expressions and JSON Schema, this demo focuses on regular expressions. For JSON Schema + Pydantic, see the sample Pydantic program notebook.
If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙.
In [ ]:
Copied!
%pip install llama-index-llms-llama-cpp
%pip install llama-index-llms-llama-cpp
In [ ]:
Copied!
!pip install llama-index llama-index-program-lmformatenforcer lm-format-enforcer llama-cpp-python
!pip install llama-index llama-index-program-lmformatenforcer lm-format-enforcer llama-cpp-python
In [ ]:
Copied!
import lmformatenforcer
import re
from llama_index.program.lmformatenforcer.utils import (
activate_lm_format_enforcer,
build_lm_format_enforcer_function,
)
import lmformatenforcer
import re
from llama_index.program.lmformatenforcer.utils import (
activate_lm_format_enforcer,
build_lm_format_enforcer_function,
)
Define output format
In [ ]:
Copied!
regex = r'"Hello, my name is (?P<name>[a-zA-Z]*)\. I was born in (?P<hometown>[a-zA-Z]*). Nice to meet you!"'
regex = r'"Hello, my name is (?P[a-zA-Z]*)\. I was born in (?P[a-zA-Z]*). Nice to meet you!"'
Create the model. We use LlamaCPP as the LLM in this demo, but HuggingFaceLLM is also supported.
In [ ]:
Copied!
from llama_index.llms.llama_cpp import LlamaCPP
llm = LlamaCPP()
from llama_index.llms.llama_cpp import LlamaCPP
llm = LlamaCPP()
llama_model_loader: loaded meta data with 19 key-value pairs and 363 tensors from /mnt/wsl/PHYSICALDRIVE1p3/llama_index/models/llama-2-13b-chat.Q4_0.gguf (version GGUF V2 (latest)) llama_model_loader: - tensor 0: token_embd.weight q4_0 [ 5120, 32000, 1, 1 ] llama_model_loader: - tensor 1: blk.0.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 2: blk.0.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 3: blk.0.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 4: blk.0.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 5: blk.0.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 6: blk.0.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 7: blk.0.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 8: blk.0.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 9: blk.0.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 10: blk.1.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 11: blk.1.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 12: blk.1.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 13: blk.1.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 14: blk.1.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 15: blk.1.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 16: blk.1.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 17: blk.1.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 18: blk.1.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 19: blk.10.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 20: blk.10.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 21: blk.10.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 22: blk.10.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 23: blk.10.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 24: blk.10.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 25: blk.10.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 26: blk.10.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 27: blk.10.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 28: blk.11.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 29: blk.11.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 30: blk.11.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 31: blk.11.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 32: blk.11.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 33: blk.11.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 34: blk.11.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 35: blk.11.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 36: blk.11.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 37: blk.12.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 38: blk.12.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 39: blk.12.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 40: blk.12.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 41: blk.12.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 42: blk.12.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 43: blk.12.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 44: blk.12.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 45: blk.12.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 46: blk.13.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 47: blk.13.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 48: blk.13.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 49: blk.13.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 50: blk.13.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 51: blk.13.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 52: blk.13.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 53: blk.13.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 54: blk.13.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 55: blk.14.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 56: blk.14.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 57: blk.14.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 58: blk.14.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 59: blk.14.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 60: blk.14.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 61: blk.14.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 62: blk.14.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 63: blk.14.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 64: blk.15.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 65: blk.15.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 66: blk.2.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 67: blk.2.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 68: blk.2.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 69: blk.2.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 70: blk.2.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 71: blk.2.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 72: blk.2.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 73: blk.2.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 74: blk.2.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 75: blk.3.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 76: blk.3.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 77: blk.3.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 78: blk.3.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 79: blk.3.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 80: blk.3.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 81: blk.3.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 82: blk.3.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 83: blk.3.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 84: blk.4.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 85: blk.4.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 86: blk.4.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 87: blk.4.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 88: blk.4.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 89: blk.4.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 90: blk.4.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 91: blk.4.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 92: blk.4.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 93: blk.5.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 94: blk.5.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 95: blk.5.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 96: blk.5.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 97: blk.5.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 98: blk.5.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 99: blk.5.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 100: blk.5.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 101: blk.5.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 102: blk.6.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 103: blk.6.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 104: blk.6.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 105: blk.6.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 106: blk.6.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 107: blk.6.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 108: blk.6.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 109: blk.6.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 110: blk.6.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 111: blk.7.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 112: blk.7.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 113: blk.7.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 114: blk.7.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 115: blk.7.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 116: blk.7.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 117: blk.7.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 118: blk.7.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 119: blk.7.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 120: blk.8.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 121: blk.8.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 122: blk.8.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 123: blk.8.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 124: blk.8.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 125: blk.8.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 126: blk.8.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 127: blk.8.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 128: blk.8.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 129: blk.9.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 130: blk.9.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 131: blk.9.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 132: blk.9.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 133: blk.9.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 134: blk.9.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 135: blk.9.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 136: blk.9.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 137: blk.9.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 138: blk.15.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 139: blk.15.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 140: blk.15.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 141: blk.15.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 142: blk.15.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 143: blk.15.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 144: blk.15.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 145: blk.16.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 146: blk.16.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 147: blk.16.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 148: blk.16.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 149: blk.16.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 150: blk.16.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 151: blk.16.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 152: blk.16.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 153: blk.16.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 154: blk.17.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 155: blk.17.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 156: blk.17.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 157: blk.17.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 158: blk.17.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 159: blk.17.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 160: blk.17.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 161: blk.17.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 162: blk.17.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 163: blk.18.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 164: blk.18.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 165: blk.18.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 166: blk.18.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 167: blk.18.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 168: blk.18.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 169: blk.18.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 170: blk.18.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 171: blk.18.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 172: blk.19.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 173: blk.19.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 174: blk.19.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 175: blk.19.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 176: blk.19.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 177: blk.19.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 178: blk.19.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 179: blk.19.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 180: blk.19.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 181: blk.20.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 182: blk.20.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 183: blk.20.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 184: blk.20.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 185: blk.20.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 186: blk.20.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 187: blk.20.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 188: blk.20.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 189: blk.20.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 190: blk.21.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 191: blk.21.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 192: blk.21.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 193: blk.21.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 194: blk.21.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 195: blk.21.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 196: blk.21.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 197: blk.21.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 198: blk.21.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 199: blk.22.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 200: blk.22.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 201: blk.22.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 202: blk.22.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 203: blk.22.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 204: blk.22.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 205: blk.22.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 206: blk.22.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 207: blk.22.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 208: blk.23.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 209: blk.23.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 210: blk.23.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 211: blk.23.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 212: blk.23.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 213: blk.23.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 214: blk.23.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 215: blk.23.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 216: blk.23.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 217: blk.24.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 218: blk.24.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 219: blk.24.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 220: blk.24.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 221: blk.24.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 222: blk.24.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 223: blk.24.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 224: blk.24.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 225: blk.24.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 226: blk.25.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 227: blk.25.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 228: blk.25.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 229: blk.25.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 230: blk.25.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 231: blk.25.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 232: blk.25.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 233: blk.25.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 234: blk.25.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 235: blk.26.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 236: blk.26.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 237: blk.26.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 238: blk.26.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 239: blk.26.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 240: blk.26.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 241: blk.26.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 242: blk.26.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 243: blk.26.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 244: blk.27.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 245: blk.27.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 246: blk.27.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 247: blk.27.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 248: blk.27.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 249: blk.27.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 250: blk.27.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 251: blk.27.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 252: blk.27.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 253: blk.28.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 254: blk.28.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 255: blk.28.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 256: blk.28.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 257: blk.28.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 258: blk.28.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 259: blk.28.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 260: blk.28.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 261: blk.28.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 262: blk.29.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 263: blk.29.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 264: blk.29.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 265: blk.29.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 266: blk.29.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 267: blk.29.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 268: blk.29.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 269: blk.29.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 270: blk.29.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 271: blk.30.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 272: blk.30.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 273: blk.30.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 274: blk.30.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 275: blk.30.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 276: blk.30.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 277: output.weight q6_K [ 5120, 32000, 1, 1 ] llama_model_loader: - tensor 278: blk.30.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 279: blk.30.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 280: blk.30.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 281: blk.31.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 282: blk.31.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 283: blk.31.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 284: blk.31.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 285: blk.31.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 286: blk.31.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 287: blk.31.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 288: blk.31.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 289: blk.31.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 290: blk.32.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 291: blk.32.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 292: blk.32.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 293: blk.32.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 294: blk.32.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 295: blk.32.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 296: blk.32.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 297: blk.32.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 298: blk.32.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 299: blk.33.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 300: blk.33.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 301: blk.33.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 302: blk.33.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 303: blk.33.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 304: blk.33.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 305: blk.33.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 306: blk.33.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 307: blk.33.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 308: blk.34.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 309: blk.34.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 310: blk.34.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 311: blk.34.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 312: blk.34.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 313: blk.34.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 314: blk.34.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 315: blk.34.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 316: blk.34.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 317: blk.35.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 318: blk.35.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 319: blk.35.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 320: blk.35.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 321: blk.35.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 322: blk.35.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 323: blk.35.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 324: blk.35.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 325: blk.35.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 326: blk.36.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 327: blk.36.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 328: blk.36.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 329: blk.36.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 330: blk.36.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 331: blk.36.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 332: blk.36.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 333: blk.36.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 334: blk.36.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 335: blk.37.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 336: blk.37.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 337: blk.37.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 338: blk.37.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 339: blk.37.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 340: blk.37.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 341: blk.37.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 342: blk.37.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 343: blk.37.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 344: blk.38.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 345: blk.38.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 346: blk.38.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 347: blk.38.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 348: blk.38.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 349: blk.38.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 350: blk.38.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 351: blk.38.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 352: blk.38.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 353: blk.39.attn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 354: blk.39.ffn_down.weight q4_0 [ 13824, 5120, 1, 1 ] llama_model_loader: - tensor 355: blk.39.ffn_gate.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 356: blk.39.ffn_up.weight q4_0 [ 5120, 13824, 1, 1 ] llama_model_loader: - tensor 357: blk.39.ffn_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - tensor 358: blk.39.attn_k.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 359: blk.39.attn_output.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 360: blk.39.attn_q.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 361: blk.39.attn_v.weight q4_0 [ 5120, 5120, 1, 1 ] llama_model_loader: - tensor 362: output_norm.weight f32 [ 5120, 1, 1, 1 ] llama_model_loader: - kv 0: general.architecture str llama_model_loader: - kv 1: general.name str llama_model_loader: - kv 2: llama.context_length u32 llama_model_loader: - kv 3: llama.embedding_length u32 llama_model_loader: - kv 4: llama.block_count u32 llama_model_loader: - kv 5: llama.feed_forward_length u32 llama_model_loader: - kv 6: llama.rope.dimension_count u32 llama_model_loader: - kv 7: llama.attention.head_count u32 llama_model_loader: - kv 8: llama.attention.head_count_kv u32 llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32 llama_model_loader: - kv 10: general.file_type u32 llama_model_loader: - kv 11: tokenizer.ggml.model str llama_model_loader: - kv 12: tokenizer.ggml.tokens arr llama_model_loader: - kv 13: tokenizer.ggml.scores arr llama_model_loader: - kv 14: tokenizer.ggml.token_type arr llama_model_loader: - kv 15: tokenizer.ggml.bos_token_id u32 llama_model_loader: - kv 16: tokenizer.ggml.eos_token_id u32 llama_model_loader: - kv 17: tokenizer.ggml.unknown_token_id u32 llama_model_loader: - kv 18: general.quantization_version u32 llama_model_loader: - type f32: 81 tensors llama_model_loader: - type q4_0: 281 tensors llama_model_loader: - type q6_K: 1 tensors llm_load_print_meta: format = GGUF V2 (latest) llm_load_print_meta: arch = llama llm_load_print_meta: vocab type = SPM llm_load_print_meta: n_vocab = 32000 llm_load_print_meta: n_merges = 0 llm_load_print_meta: n_ctx_train = 4096 llm_load_print_meta: n_embd = 5120 llm_load_print_meta: n_head = 40 llm_load_print_meta: n_head_kv = 40 llm_load_print_meta: n_layer = 40 llm_load_print_meta: n_rot = 128 llm_load_print_meta: n_gqa = 1 llm_load_print_meta: f_norm_eps = 0.0e+00 llm_load_print_meta: f_norm_rms_eps = 1.0e-05 llm_load_print_meta: n_ff = 13824 llm_load_print_meta: freq_base_train = 10000.0 llm_load_print_meta: freq_scale_train = 1 llm_load_print_meta: model type = 13B llm_load_print_meta: model ftype = mostly Q4_0 llm_load_print_meta: model params = 13.02 B llm_load_print_meta: model size = 6.86 GiB (4.53 BPW) llm_load_print_meta: general.name = LLaMA v2 llm_load_print_meta: BOS token = 1 '<s>' llm_load_print_meta: EOS token = 2 '</s>' llm_load_print_meta: UNK token = 0 '<unk>' llm_load_print_meta: LF token = 13 '<0x0A>' llm_load_tensors: ggml ctx size = 0.12 MB llm_load_tensors: mem required = 7024.01 MB ................................................................................................... llama_new_context_with_model: n_ctx = 3900 llama_new_context_with_model: freq_base = 10000.0 llama_new_context_with_model: freq_scale = 1 llama_new_context_with_model: kv self size = 3046.88 MB llama_new_context_with_model: compute buffer total size = 348.18 MB AVX = 1 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 0 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 |
Activate the format enforcer and run the LLM get structured output in the desired regular expression format. As long as we are inside the with activate_lm_format_enforcer(...) block, the LLM will output the desired format.
If we would have used lmformatenforcer.JsonSchemaParser and a JSON schema, we would have gotten JSON output instead.
In [ ]:
Copied!
regex_parser = lmformatenforcer.RegexParser(regex)
lm_format_enforcer_fn = build_lm_format_enforcer_function(llm, regex_parser)
with activate_lm_format_enforcer(llm, lm_format_enforcer_fn):
output = llm.complete(
"Here is a way to present myself, if my name was John and I born in Boston: "
)
regex_parser = lmformatenforcer.RegexParser(regex)
lm_format_enforcer_fn = build_lm_format_enforcer_function(llm, regex_parser)
with activate_lm_format_enforcer(llm, lm_format_enforcer_fn):
output = llm.complete(
"Here is a way to present myself, if my name was John and I born in Boston: "
)
llama_print_timings: load time = 2709.44 ms llama_print_timings: sample time = 7.26 ms / 22 runs ( 0.33 ms per token, 3031.56 tokens per second) llama_print_timings: prompt eval time = 2709.40 ms / 21 tokens ( 129.02 ms per token, 7.75 tokens per second) llama_print_timings: eval time = 3047.28 ms / 21 runs ( 145.11 ms per token, 6.89 tokens per second) llama_print_timings: total time = 5965.41 ms
The output is a string, according to the regular expression, which we can parse and extract parameters from.
In [ ]:
Copied!
print(output)
print(re.match(regex, output.text).groupdict())
print(output)
print(re.match(regex, output.text).groupdict())
"Hello, my name is John. I was born in Boston, Nice to meet you!"
{'name': 'John', 'hometown': 'Boston'}
