TheBloke

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Mistral-7B-Instruct-v0.1-AWQ

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I am having the same problem

@Lord-Goku Please use model.model instead of just model for model argument of the pipeline method.
Ex:

from transformers import pipeline

pipe = pipeline(
    "text-generation",
    model=model.model,
    tokenizer=tokenizer,
    max_new_tokens=512,
    do_sample=True,
    temperature=0.7,
    top_p=0.95,
    top_k=40,
    repetition_penalty=1.1,
)

print(pipe(prompt)[0]["generated_text"])

That works? Nice, thanks @RaviNaik !

Note that very soon there will be native support for AWQ in Transformers, and then pipeline should work as normal without special steps needed.

Yeah it works @TheBloke , tested it out with TheBloke/Mistral-7B-Instruct-v0.1-AWQ.
One more issue I noticed is that AutoAWQForCausalLM.from_quantized by default loads the model into cuda:0 or device0 and it looks like there is no device_map kind of argument we can pass to specify the device index. Hope these issues will be solved once AWQ is natively supported in Transformers.