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metadata
library_name: pruna-engine
thumbnail: >-
  https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg
metrics:
  - memory_disk
  - memory_inference
  - inference_latency
  - inference_throughput
  - inference_CO2_emissions
  - inference_energy_consumption

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Simply make AI models cheaper, smaller, faster, and greener!

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  • Read the documentations to know more here
  • Join Pruna AI community on Discord here to share feedback/suggestions or get help.

Frequently Asked Questions

  • How does the compression work? The model is compressed by using bitsandbytes.
  • 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/Mistral-7B-Instruct-v0.2-bnb-4bit"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    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 mistralai/Mistral-7B-Instruct-v0.2 before using this model which provided the base model. The license of the pruna-engine is here on Pypi.

Want to compress other models?

  • Contact us and tell us which model to compress next here.
  • Request access to easily compress your own AI models here.