metadata

language:
  - en
license: apache-2.0
library_name: transformers
tags:
  - orpo
  - Phi 3
base_model:
  - microsoft/Phi-3-mini-128k-instruct
datasets:
  - mlabonne/orpo-dpo-mix-40k

Orpo-Phi3-3B-128K

This is an ORPO fine-tune of microsoft/Phi-3-mini-128k-instruct on 10k samples of mlabonne/orpo-dpo-mix-40k.

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Muhammad2003/Orpo-Phi3-3B-128K"
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,
    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"])

📈 Training curves

Wandb Report

🏆 Evaluation

Coming Soon!