paper-qa
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20 hours ago •
Future-House
Future-House
Local LLM ISSUE GGML_ASSERT
I'm running on windows 10 cpu only no gpu
Error: GGML_ASSERT: C:\Users\user\AppData\Local\Temp\pip-install-l0_yao9s\llama-cpp-python_686671b6d7b8440a98e23acb5bc6a41a\vendor\llama.cpp\ggml.c:15149: cgraph->nodes[cgraph->n_nodes - 1] == tensor GGML_ASSERT: C:\Users\user\AppData\Local\Temp\pip-install-l0_yao9s\llama-cpp-python_686671b6d7b8440a98e23acb5bc6a41a\vendor\llama.cpp\ggml.c:4326: ggml_nelements(a) == (ne0ne1ne2*ne3)
Repeated trials yield same results. Local llm: TheBloke/Llama-2-7B-Chat-GGUF (llama-2-7b-chat.Q6_K.gguf) Embedding: BAAI/bge-large-en-v1.5
import os
os.environ['OPENAI_API_KEY'] = 'dummy_key'
# import paperscraper
from paperqa import Docs
from langchain.llms.llamacpp import LlamaCpp
from langchain.prompts import PromptTemplate
from langchain.chains import LLMChain
from langchain.callbacks.manager import CallbackManager
from langchain.embeddings import LlamaCppEmbeddings
from langchain.embeddings import HuggingFaceBgeEmbeddings
from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
# Make sure the model path is correct for your system!
llm = LlamaCpp(
model_path="C:/paper-qa/models/llama-2-7b-chat.Q6_K.gguf", callbacks=[StreamingStdOutCallbackHandler()],
)
model_name = "BAAI/bge-large-en-v1.5"
model_kwargs = {'device': 'cpu'}
encode_kwargs = {'normalize_embeddings': True}
embeddings = HuggingFaceBgeEmbeddings(
model_name=model_name,
# model_kwargs=model_kwargs,
# encode_kwargs=encode_kwargs,
cache_folder="C:\paper-qa\models"
)
# embeddings = LlamaCppEmbeddings(
# model_path="C:/paper-qa/models/bge-large-en-v1_5_pytorch_model.bin"
# )
# model_name = "BAAI/bge-large-en-v1.5"
# model_kwargs = {'device': 'cpu'}
# encode_kwargs = {'normalize_embeddings': False}
# hf = HuggingFaceEmbeddings(
# model_name=model_name,
# model_kwargs=model_kwargs,
# encode_kwargs=encode_kwargs
# )
docs = Docs(llm=llm, embeddings=embeddings)
# keyword_search = 'bispecific antibody manufacture'
# papers = paperscraper.search_papers(keyword_search, limit=2)
# for path,data in papers.items():
# try:
# docs.add(path,chunk_chars=500)
# except ValueError as e:
# print('Could not read', path, e)
path = "C:\\paper-qa\\Source\\The Encyclopedia of the Cold War_90-95.pdf"
print("Before adding document")
docs.add(path,chunk_chars=500)
print("Document added")
answer = docs.query("Summarize 2 interesting events of the cold war from the book.")
print("Queried.")
print(answer)
whole output
llama_model_loader: loaded meta data with 19 key-value pairs and 291 tensors from C:/paper-qa/models/llama-2-7b-chat.Q6_K.gguf (version GGUF V2)
llama_model_loader: - tensor 0: token_embd.weight q6_K [ 4096, 32000,
1, 1 ]
llama_model_loader: - tensor 1: blk.0.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 2: blk.0.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 3: blk.0.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 4: blk.0.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 5: blk.0.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 6: blk.0.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 7: blk.0.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 8: blk.0.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 9: blk.0.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 10: blk.1.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 11: blk.1.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 12: blk.1.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 13: blk.1.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 14: blk.1.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 15: blk.1.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 16: blk.1.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 17: blk.1.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 18: blk.1.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 19: blk.10.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 20: blk.10.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 21: blk.10.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 22: blk.10.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 23: blk.10.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 24: blk.10.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 25: blk.10.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 26: blk.10.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 27: blk.10.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 28: blk.11.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 29: blk.11.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 30: blk.11.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 31: blk.11.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 32: blk.11.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 33: blk.11.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 34: blk.11.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 35: blk.11.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 36: blk.11.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 37: blk.12.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 38: blk.12.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 39: blk.12.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 40: blk.12.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 41: blk.12.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 42: blk.12.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 43: blk.12.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 44: blk.12.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 45: blk.12.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 46: blk.13.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 47: blk.13.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 48: blk.13.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 49: blk.13.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 50: blk.13.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 51: blk.13.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 52: blk.13.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 53: blk.13.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 54: blk.13.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 55: blk.14.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 56: blk.14.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 57: blk.14.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 58: blk.14.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 59: blk.14.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 60: blk.14.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 61: blk.14.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 62: blk.14.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 63: blk.14.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 64: blk.15.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 65: blk.15.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 66: blk.15.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 67: blk.15.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 68: blk.15.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 69: blk.15.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 70: blk.15.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 71: blk.15.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 72: blk.15.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 73: blk.16.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 74: blk.16.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 75: blk.16.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 76: blk.16.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 77: blk.16.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 78: blk.16.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 79: blk.16.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 80: blk.16.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 81: blk.16.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 82: blk.17.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 83: blk.17.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 84: blk.17.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 85: blk.17.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 86: blk.17.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 87: blk.17.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 88: blk.17.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 89: blk.17.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 90: blk.17.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 91: blk.18.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 92: blk.18.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 93: blk.18.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 94: blk.18.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 95: blk.18.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 96: blk.18.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 97: blk.18.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 98: blk.18.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 99: blk.18.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 100: blk.19.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 101: blk.19.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 102: blk.19.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 103: blk.19.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 104: blk.19.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 105: blk.19.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 106: blk.19.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 107: blk.19.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 108: blk.19.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 109: blk.2.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 110: blk.2.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 111: blk.2.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 112: blk.2.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 113: blk.2.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 114: blk.2.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 115: blk.2.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 116: blk.2.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 117: blk.2.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 118: blk.20.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 119: blk.20.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 120: blk.20.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 121: blk.20.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 122: blk.20.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 123: blk.20.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 124: blk.20.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 125: blk.20.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 126: blk.20.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 127: blk.21.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 128: blk.21.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 129: blk.21.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 130: blk.21.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 131: blk.21.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 132: blk.21.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 133: blk.21.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 134: blk.21.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 135: blk.21.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 136: blk.22.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 137: blk.22.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 138: blk.22.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 139: blk.22.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 140: blk.22.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 141: blk.22.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 142: blk.22.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 143: blk.22.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 144: blk.22.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 145: blk.23.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 146: blk.23.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 147: blk.23.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 148: blk.23.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 149: blk.23.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 150: blk.23.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 151: blk.23.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 152: blk.23.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 153: blk.23.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 154: blk.3.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 155: blk.3.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 156: blk.3.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 157: blk.3.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 158: blk.3.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 159: blk.3.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 160: blk.3.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 161: blk.3.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 162: blk.3.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 163: blk.4.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 164: blk.4.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 165: blk.4.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 166: blk.4.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 167: blk.4.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 168: blk.4.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 169: blk.4.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 170: blk.4.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 171: blk.4.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 172: blk.5.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 173: blk.5.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 174: blk.5.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 175: blk.5.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 176: blk.5.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 177: blk.5.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 178: blk.5.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 179: blk.5.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 180: blk.5.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 181: blk.6.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 182: blk.6.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 183: blk.6.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 184: blk.6.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 185: blk.6.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 186: blk.6.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 187: blk.6.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 188: blk.6.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 189: blk.6.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 190: blk.7.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 191: blk.7.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 192: blk.7.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 193: blk.7.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 194: blk.7.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 195: blk.7.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 196: blk.7.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 197: blk.7.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 198: blk.7.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 199: blk.8.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 200: blk.8.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 201: blk.8.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 202: blk.8.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 203: blk.8.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 204: blk.8.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 205: blk.8.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 206: blk.8.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 207: blk.8.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 208: blk.9.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 209: blk.9.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 210: blk.9.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 211: blk.9.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 212: blk.9.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 213: blk.9.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 214: blk.9.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 215: blk.9.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 216: blk.9.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 217: output.weight q6_K [ 4096, 32000,
1, 1 ]
llama_model_loader: - tensor 218: blk.24.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 219: blk.24.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 220: blk.24.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 221: blk.24.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 222: blk.24.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 223: blk.24.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 224: blk.24.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 225: blk.24.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 226: blk.24.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 227: blk.25.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 228: blk.25.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 229: blk.25.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 230: blk.25.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 231: blk.25.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 232: blk.25.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 233: blk.25.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 234: blk.25.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 235: blk.25.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 236: blk.26.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 237: blk.26.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 238: blk.26.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 239: blk.26.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 240: blk.26.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 241: blk.26.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 242: blk.26.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 243: blk.26.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 244: blk.26.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 245: blk.27.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 246: blk.27.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 247: blk.27.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 248: blk.27.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 249: blk.27.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 250: blk.27.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 251: blk.27.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 252: blk.27.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 253: blk.27.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 254: blk.28.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 255: blk.28.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 256: blk.28.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 257: blk.28.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 258: blk.28.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 259: blk.28.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 260: blk.28.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 261: blk.28.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 262: blk.28.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 263: blk.29.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 264: blk.29.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 265: blk.29.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 266: blk.29.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 267: blk.29.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 268: blk.29.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 269: blk.29.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 270: blk.29.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 271: blk.29.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 272: blk.30.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 273: blk.30.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 274: blk.30.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 275: blk.30.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 276: blk.30.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 277: blk.30.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 278: blk.30.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 279: blk.30.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 280: blk.30.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 281: blk.31.attn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 282: blk.31.ffn_down.weight q6_K [ 11008, 4096,
1, 1 ]
llama_model_loader: - tensor 283: blk.31.ffn_gate.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 284: blk.31.ffn_up.weight q6_K [ 4096, 11008,
1, 1 ]
llama_model_loader: - tensor 285: blk.31.ffn_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - tensor 286: blk.31.attn_k.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 287: blk.31.attn_output.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 288: blk.31.attn_q.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 289: blk.31.attn_v.weight q6_K [ 4096, 4096,
1, 1 ]
llama_model_loader: - tensor 290: output_norm.weight f32 [ 4096, 1,
1, 1 ]
llama_model_loader: - kv 0: general.architecture str = llama
llama_model_loader: - kv 1: general.name str = LLaMA v2
llama_model_loader: - kv 2: llama.context_length u32 = 4096
llama_model_loader: - kv 3: llama.embedding_length u32 = 4096
llama_model_loader: - kv 4: llama.block_count u32 = 32llama_model_loader: - kv 5: llama.feed_forward_length u32 = 11008
llama_model_loader: - kv 6: llama.rope.dimension_count u32 = 128
llama_model_loader: - kv 7: llama.attention.head_count u32 = 32llama_model_loader: - kv 8: llama.attention.head_count_kv u32 = 32llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 10: general.file_type u32 = 18llama_model_loader: - kv 11: tokenizer.ggml.model str = llama
llama_model_loader: - kv 12: tokenizer.ggml.tokens arr[str,32000] = ["<unk>", "<s>", "</s>", "<0x00>", "<...
llama_model_loader: - kv 13: tokenizer.ggml.scores arr[f32,32000] = [0.000000, 0.000000, 0.000000, 0.0000...
llama_model_loader: - kv 14: tokenizer.ggml.token_type arr[i32,32000] = [2, 3, 3, 6, 6, 6, 6, 6, 6, 6, 6, 6, ...
llama_model_loader: - kv 15: tokenizer.ggml.bos_token_id u32 = 1
llama_model_loader: - kv 16: tokenizer.ggml.eos_token_id u32 = 2
llama_model_loader: - kv 17: tokenizer.ggml.unknown_token_id u32 = 0
llama_model_loader: - kv 18: general.quantization_version u32 = 2
llama_model_loader: - type f32: 65 tensors
llama_model_loader: - type q6_K: 226 tensors
llm_load_vocab: special tokens definition check successful ( 259/32000 ).
llm_load_print_meta: format = GGUF V2
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 = 4096
llm_load_print_meta: n_head = 32
llm_load_print_meta: n_head_kv = 32
llm_load_print_meta: n_layer = 32
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-06
llm_load_print_meta: f_clamp_kqv = 0.0e+00
llm_load_print_meta: f_max_alibi_bias = 0.0e+00
llm_load_print_meta: n_ff = 11008
llm_load_print_meta: rope scaling = linear
llm_load_print_meta: freq_base_train = 10000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_yarn_orig_ctx = 4096
llm_load_print_meta: rope_finetuned = unknown
llm_load_print_meta: model type = 7B
llm_load_print_meta: model ftype = mostly Q6_K
llm_load_print_meta: model params = 6.74 B
llm_load_print_meta: model size = 5.15 GiB (6.56 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 = 0.11 MiB
llm_load_tensors: mem required = 5272.45 MiB
....................................................................................................
llama_new_context_with_model: n_ctx = 512
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 = 256.00 MiB
llama_build_graph: non-view tensors processed: 740/740
llama_new_context_with_model: compute buffer total size = 4.16 MiB
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 = 0 | VSX = 0
|
Before adding document
Abdullah I of Jordan. "Soldier, Diplomat, and King of Jordan." The Oxford Encyclopedia of the
Modern World, vol. 1, Oxford University Press, 2023, pp. 56-57.
llama_print_timings: load time = 7311.60 ms
llama_print_timings: sample time = 18.23 ms / 55 runs ( 0.33 ms per token,
3016.67 tokens per second)
llama_print_timings: prompt eval time = 53923.10 ms / 190 tokens ( 283.81 ms per token,
3.52 tokens per second)
llama_print_timings: eval time = 19552.25 ms / 54 runs ( 362.08 ms per token,
2.76 tokens per second)
llama_print_timings: total time = 73785.66 ms
Document added
Llama.generate: prefix-match hit
Llama.generate: prefix-match hit
Llama.generate: prefix-match hit
Llama.generate: prefix-match hit
Llama.generate: prefix-match hit
GGML_ASSERT: C:\Users\user\AppData\Local\Temp\pip-install-l0_yao9s\llama-cpp-python_686671b6d7b8440a98e23acb5bc6a41a\vendor\llama.cpp\ggml.c:15149: cgraph->nodes[cgraph->n_nodes - 1] == tensor
GGML_ASSERT: C:\Users\user\AppData\Local\Temp\pip-install-l0_yao9s\llama-cpp-python_686671b6d7b8440a98e23acb5bc6a41a\vendor\llama.cpp\ggml.c:4326: ggml_nelements(a) == (ne0*ne1*ne2*ne3)
PS C:\paper-qa>
Hello everyone, we have just released version 5, which completely outsources all LLM management to https://github.com/BerriAI/litellm.
If your issue persists, please reopen a new issue using paper-qa>=5
