Update README.md

README.md

@@ -1,46 +1,48 @@
----
-language: en
-tags:
-- gpt2
-- text-generation
-license: mit
----
-
-# QnQGPT Model
-
-This is a custom GPT model based on GPT-2 architecture.
-
-## Model Details
-
-- Model Type: GPT-2
-- Base Model: gpt2
-- Training Data: [Describe your training data]
-- Use Cases: [Describe intended use cases]
-
-## Usage
-
-```python
-from transformers import AutoModelForCausalLM, AutoTokenizer
-
-model = AutoModelForCausalLM.from_pretrained("karthikqnq/qnqgpt")
-tokenizer = AutoTokenizer.from_pretrained("karthikqnq/qnqgpt")
-
-# Generate text
-text = "Hello, how are"
-inputs = tokenizer(text, return_tensors="pt")
-outputs = model.generate(**inputs, max_length=50)
-result = tokenizer.decode(outputs[0])
-print(result)
-```
-
-## Training Details
-
-[Add your training details here]
-
-## Limitations
-
-[Add model limitations here]
-
-## License
-
-This model is released under the MIT License.
+---
+language: en
+tags:
+- gpt2
+- text-generation
+license: mit
+base_model:
+- openai-community/gpt2
+---
+
+# QnQGPT Model
+
+This is a custom GPT model based on GPT-2 architecture.
+
+## Model Details
+
+- Model Type: GPT-2
+- Base Model: gpt2
+- Training Data: [Describe your training data]
+- Use Cases: [Describe intended use cases]
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("karthikqnq/qnqgpt")
+tokenizer = AutoTokenizer.from_pretrained("karthikqnq/qnqgpt")
+
+# Generate text
+text = "Hello, how are"
+inputs = tokenizer(text, return_tensors="pt")
+outputs = model.generate(**inputs, max_length=50)
+result = tokenizer.decode(outputs[0])
+print(result)
+```
+
+## Training Details
+
+[Add your training details here]
+
+## Limitations
+
+[Add model limitations here]
+
+## License
+
+This model is released under the MIT License.