Create README.md

README.md

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+---
+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:
+
+```python
+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())