metadata

license: apache-2.0
datasets:
  - Anthropic/hh-rlhf
language:
  - en
pipeline_tag: text-generation

GPT-2 Medium Fine-Tuned on Anthropic-hh Dataset

This repository houses a GPT-2 Medium model fine-tuned on the Anthropic-hh dataset. The fine-tuning process involved masking Human's utterances, with the loss computed exclusively on the Assistant's responses.

Model Information

Base Model: GPT-2 Medium
Training Data: Anthropic-hh dataset
Fine-Tuning Approach: Supervised fine-tuning with a focus on Assistant's responses.

How to Use

from transformers import GPT2LMHeadModel, GPT2Tokenizer

# Load tokenizer and model
tokenizer = GPT2Tokenizer.from_pretrained("RaushanTurganbay/GPT2_instruct_tuned")
model = GPT2LMHeadModel.from_pretrained("RaushanTurganbay/GPT2_instruct_tuned")

# Generate responses
prompt = "Your input prompt here"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_length=150, num_return_sequences=1)

print(tokenizer.decode(outputs[0], skip_special_tokens=True))