license, datasets, language, base_model, pipeline_tag, library_name, tags

license	datasets	language	base_model	pipeline_tag	library_name	tags
apache-2.0	rahul77/rahul-gpt2-1k	en	openai-community/gpt2	text-generation	transformers	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 = "https://api-inference.huggingface.co/models/rahul77/gpt-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())