compressed-llm/llama-2-13b-chat-gptq

from transformers import AutoTokenizer
from auto_gptq import AutoGPTQForCausalLM
model_path = 'efficient-llm/llama-2-13b-chat-gptq'
tokenizer_path = 'meta-llama/Llama-2-7b-hf'
model = AutoGPTQForCausalLM.from_quantized(
        model_path,
        # inject_fused_attention=False, # or
        disable_exllama=True,
        device_map='auto',
        revision='3bit_128g',
    )
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained(tokenizer_path, trust_remote_code=True)
input_ids = tokenizer('How are you?', return_tensors='pt').input_ids.to('cuda')
outputs = model.generate(input_ids=input_ids, max_length=128)
print(tokenizer.decode(outputs[0]))