Create README.md

README.md

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+---
+tags:
+- gptq
+- 4bit
+- gptqmodel
+- modelcloud
+- llama-3.1
+- 8b
+---
+This model has been quantized using [GPTQModel](https://github.com/ModelCloud/GPTQModel).
+
+- **bits**: 4
+- **group_size**: 128
+- **desc_act**: true
+- **static_groups**: false
+- **sym**: true
+- **lm_head**: false
+- **damp_percent**: 0.01
+- **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
+import torch
+from transformers import AutoTokenizer
+from gptqmodel import GPTQModel
+
+device = torch.device("cuda:0")
+
+model_name = "ModelCloud/Meta-Llama-3.1-8B-gptq-4bit"
+
+prompt = "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)
+
+inputs = tokenizer(prompt, return_tensors="pt").to(device)
+res = model.generate(**inputs, num_beams=1, min_new_tokens=1, max_new_tokens=512)
+print(tokenizer.decode(res[0]))
+```