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README.md

@@ -1,15 +1,32 @@
+---
+license: mit
+datasets:
+  - openwebtext
+  - alpacha
+tags:
+  - text-generation
+  - gpt-2
+  - openwebtext
+  - alpacha
+model_name: gpt2-124M
+language: en
+---
+
 # GPT-2 124M Fine-tuned on OpenWebText and Alpacha
 
 This model is a fine-tuned version of GPT-2 (124M parameters) trained on the OpenWebText dataset and further fine-tuned on the Alpacha dataset.
 
 ## Model Description
+
 This model is based on the GPT-2 architecture and has been fine-tuned on a combination of two datasets:
+
 1. **OpenWebText**: The model was initially trained on the OpenWebText dataset for 600,000 iterations.
 2. **Alpacha**: The model was further fine-tuned on the Alpacha dataset for the remaining 50,000 iterations.
 
 The model was trained using a **laptop with an RTX 3060 GPU** for a total of **650,000 iterations** (approximately **8 days** of training).
 
 ## Hardware Details
+
 - **GPU**: Laptop with an **RTX 3060**
 - **Training Time**: The model took **8 days** (approximately 650,000 iterations) to train.
 - **Total Iterations**: 650,000 iterations (600,000 on OpenWebText + 50,000 on Alpacha).
@@ -29,3 +46,4 @@ inputs = tokenizer(input_text, return_tensors="pt")
 outputs = model.generate(**inputs)
 
 print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```