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ModelCloud/Mistral-Large-Instruct-2407-gptq-4bit

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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Model Card

This model has been quantized using GPTQModel.

  • —bits: 4
  • —group_size: 128
  • —desc_act: true
  • —static_groups: false
  • —sym: true
  • —lm_head: false
  • —damp_percent: 0.0025
  • —true_sequential: true
  • —model_name_or_path: ""
  • —model_file_base_name: "model"
  • —quant_method: "gptq"
  • —checkpoint_format: "gptq"
  • —meta：
  • —quantizer: "gptqmodel:0.9.9-dev0"

Here is an example:

python
from transformers import AutoTokenizer
from gptqmodel import GPTQModel

model_name = "ModelCloud/Mistral-Large-Instruct-2407-gptq-4bit"

prompt = [{"role": "user", "content": "I am in Shanghai, preparing to visit the natural history museum. Can you tell me the best way to"}]

tokenizer = AutoTokenizer.from_pretrained(model_name)

model = GPTQModel.from_quantized(model_name)

input_tensor = tokenizer.apply_chat_template(prompt, add_generation_prompt=True, return_tensors="pt")
outputs = model.generate(input_ids=input_tensor.to(model.device), max_new_tokens=100)
result = tokenizer.decode(outputs[0][input_tensor.shape[1]:], skip_special_tokens=True)

print(result)