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mistral-7b-instruct-v0.1-awq

Text Generation
Transformers
PyTorch
mistral
text-generation-inference
Inference Endpoints
4-bit precision
awq
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mistral-7b-instruct-v0.1-awq / README.md
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license: apache-2.0

Mistral 7B Instruct

AWQ quantized model.

Dependencies:

pip install git+https://github.com/huggingface/transformers.git
pip install git+https://github.com/casper-hansen/AutoAWQ.git

Example:

from awq import AutoAWQForCausalLM
from transformers import AutoTokenizer, TextStreamer

quant_path = "mistral-7b-instruct-v0.1"

# Load model
model = AutoAWQForCausalLM.from_quantized(quant_path, fuse_layers=True)
tokenizer = AutoTokenizer.from_pretrained(quant_path, trust_remote_code=True)
streamer = TextStreamer(tokenizer, skip_special_tokens=True)

# Convert prompt to tokens
text = "<s>[INST] What is your favourite condiment? [/INST]"
"Well, I'm quite partial to a good squeeze of fresh lemon juice. It adds just the right amount of zesty flavour to whatever I'm cooking up in the kitchen!</s> "
"[INST] Do you have mayonnaise recipes? [/INST]"

tokens = tokenizer(
    text, 
    return_tensors='pt'
).input_ids.cuda()

# Generate output
generation_output = model.generate(
    tokens, 
    streamer=streamer,
    max_new_tokens=512
)