a-k-aAiMGoD/phi3-mini-distributed-fine-tune

Fine-tuned Phi-3-mini Model

This is a fine-tuned version of microsoft/Phi-3-mini-128k-instruct using distributed training.

Model Details

• —Base Model: microsoft/Phi-3-mini-128k-instruct
• —Training Method: Distributed fine-tuning with Ray
• —Shards Used: 2
• —Parameters: ~3.8B

Training Information

The model was fine-tuned using a distributed approach across multiple shards. While the base architecture is preserved, this model has been through a fine-tuning process optimized for specific tasks.

Usage

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("a-k-aAiMGoD/phi3-mini-distributed-fine-tune")
model = AutoModelForCausalLM.from_pretrained("a-k-aAiMGoD/phi3-mini-distributed-fine-tune")

# Example usage
text = "Hello, how are you?"
inputs = tokenizer(text, return_tensors="pt")
outputs = model.generate(**inputs, max_length=100)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)

Training Configuration

• —Distributed across 2 shards
• —Optimized for large-scale deployment
• —Enhanced with Ray-based parallelization