metadata

license: apache-2.0
datasets:
  - rahul77/rahul-gpt2-1k
language:
  - en
base_model: openai-community/gpt2
pipeline_tag: text-generation
library_name: transformers
tags:
  - text-generation
  - GPT-2
  - fine-tuned
  - language-model
  - transformers

GPT-2 Fine-Tuned Model

This is a fine-tuned version of the GPT-2 model designed for text generation tasks. The model has been fine-tuned to improve its performance on generating coherent and contextually relevant text.

Model Details

Model Name: GPT-2 Fine-Tuned
Base Model: gpt2
Architecture: GPT2LMHeadModel
Tokenization: Supported
- pad_token_id: 50256
- bos_token_id: 50256
- eos_token_id: 50256

Supported Tasks

This model supports the following task:

Text Generation

Configuration

Model Configuration (config.json)

Hidden Size: 768
Number of Layers: 12
Number of Attention Heads: 12
Vocab Size: 50257
Token Type IDs: Not used

Generation Configuration (generation_config.json)

Sampling Temperature: 0.7
Top-p (nucleus sampling): 0.9
Pad Token ID: 50256
Bos Token ID: 50256
Eos Token ID: 50256

Usage

To use this model for text generation via the Hugging Face API, use the following Python code snippet:

import requests

api_url = "/static-proxy?url=https%3A%2F%2Fapi-inference.huggingface.co%2Fmodels%2Frahul77%2Fgpt-2-finetune"
headers = {
    "Authorization": "Bearer YOUR_API_TOKEN",  # Replace with your Hugging Face API token
    "Content-Type": "application/json"
}

data = {
    "inputs": "What is a large language model?",
    "parameters": {
        "max_length": 50
    }
}

response = requests.post(api_url, headers=headers, json=data)

if response.status_code == 200:
    print(response.json())
else:
    print(f"Error: {response.status_code}")
    print(response.json())