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wizcat/internlm-chat-7b-v1_1-gptq
internlm-chat-7b-v1_1-gptq is a feature extraction model from wizcat. Use it when you need embeddings to search or compare text. It is set up for transformers. The card lists the license as other.
internlm-chat-7b-v11をGPTQ変換したモデルです<br 利用に当たってはhttps://huggingface.co/internlm/internlm-chat-7b-v11 のライセンスに従って下さい<br <br 推論用コード<br
Downloads · 30 days
8
3% of all-time downloads
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From the Hugging Face model README
internlm-chat-7b-v1_1をGPTQ変換したモデルです<br> 利用に当たってはhttps://huggingface.co/internlm/internlm-chat-7b-v1_1 のライセンスに従って下さい<br> <br> 推論用コード<br>
import torch
import time
from transformers import AutoTokenizer, AutoModelForCausalLM,GPTQConfig
model_path = r".\internlm-chat-7b-v1_1-gptq"
tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
gptq_config = GPTQConfig(bits= 4 , disable_exllama= True )
model = AutoModelForCausalLM.from_pretrained( model_path , device_map= "auto" , quantization_config = gptq_config,trust_remote_code=True)
model = model.eval()
history = []
while True:
txt = input("msg:")
start_time = time.perf_counter()
response, history = model.chat(tokenizer, txt, history=history)
print(response)
end_time = time.perf_counter()
elapsed_time = end_time - start_time
print(f"worktime:{elapsed_time}")