PrunaAI/mattshumer-Hermes-2-Pro-11B-GPTQ-8bit

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Frequently Asked Questions

• How does the compression work? The model is compressed by using GPTQ.
• How does the model quality change? The quality of the model output will slightly degrade.
• What is the model format? We the standard safetensors format.
• How to compress my own models? You can request premium access to more compression methods and tech support for your specific use-cases here.

Usage

from transformers import AutoTokenizer
import transformers
import torch

model = "PrunaAI/mattshumer-Hermes-2-Pro-11B-GPTQ-8bit"
tokenizer = "mattshumer/Hermes-2-Pro-11B"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(tokenizer)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    tokenizer=tokenizer,
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])

Credits & License

The license of the smashed model follows the license of the original model. Please check the license of the original model mattshumer/Hermes-2-Pro-11B before using this model which provided the base model. The license of the pruna-engine is here on Pypi.

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