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sssdddwd/
AI_Governance_Fine_Tuned_mistral_7B_LLM

Name: AI_Governance_Fine_Tuned_mistral_7B_LLM
Availability: InStock

peft

safetensors

sssdddwd/ai_regulations.csv

mistralai/Mistral-7B-Instruct-v0.1

adapter

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Mistral-7B Fine-Tuned on AI Regulations

This repository contains a fine-tuned version of the Mistral-7B-Instruct model trained on AI regulations data. The fine-tuning process utilized QLoRA (Quantized Low-Rank Adaptation) and BitsAndBytes 4-bit quantization to optimize memory efficiency while preserving performance.

Model Details

Base Model: Mistral-7B-Instruct
Fine-tuned Dataset: Custom AI regulations dataset
Quantization: 4-bit using BitsAndBytes
Training Method: QLoRA with LoRA adapters

Usage

You can use the fine-tuned model for text generation using the Hugging Face Transformers library.

Install Required Packages

pip install transformers torch bitsandbytes accelerate

Load the Model and Tokenizer

python

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

MODEL_NAME = "sssdddwd/AI_Governance_Fine_Tuned_mistral_7B_LLM"

# Load tokenizer
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)

# Load model
model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, torch_dtype=torch.float16, device_map="auto")

# Resize embeddings to match tokenizer
model.resize_token_embeddings(len(tokenizer))

# Set model to evaluation mode
model.eval()

Generate Text

python

def generate_response(prompt, max_length=256):
    inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
    outputs = model.generate(**inputs, max_length=max_length)
    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return response

# Example Usage
prompt = "What are the key AI regulations in the EU?"
response = generate_response(prompt)
print(response)

Model Training Details

Epochs: 3
Batch Size: 1 (with gradient accumulation)
Optimizer: PagedAdamW
FP16 Training: Enabled

License

This model follows the same licensing as Mistral-7B. Please refer to the official Mistral AI terms for usage restrictions.

Acknowledgments

Mistral AI for the base model.
Hugging Face for providing the ecosystem for model training and hosting.

For any questions or issues, feel free to reach out via Hugging Face discussions!