Update README.md

README.md

@@ -15,8 +15,93 @@ The above copyright notice and this permission notice shall be included in all c
 THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
 
 
+Contributions are welcome! Please fork the repository, make your changes, and submit a pull request. All contributions must follow the code style of the project.
 ---
+license: mit
+---
+
+# Nano-Butterfly Model
+
+Welcome to the `Alexander27/Nano-Butterfly` model card! This is a Causal Language Model trained using Hugging Face AutoTrain.
+
+## 🚀 How to Use
+
+You can easily run this model using the `transformers` library.
+
+### 1. Installation
+
+First, make sure you have the required libraries installed.
+
+```bash
+pip install transformers torch
+```
+
+### 2. Run the Model in Python
+
+Save the following code as a Python file (e.g., `app.py`) and run it.
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# The name of your model on the Hugging Face Hub
+model_name = "Alexander27/Nano-Butterfly"
+
+# Load the tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Define the prompt
+prompt = "The future of artificial intelligence is "
+
+# Prepare the input for the model
+input_ids = tokenizer.encode(prompt, return_tensors="pt")
+
+# Generate text
+output_sequences = model.generate(
+    input_ids=input_ids,
+    max_length=100,
+    num_return_sequences=1
+)
+
+# Decode the output and print it
+generated_text = tokenizer.decode(output_sequences[0], skip_special_tokens=True)
+
+print(generated_text)
+```
+
+Alternative in python:
+# File: app.py
+
+# 1. Install necessary libraries
+# In your terminal, run: pip install transformers torch
+
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# The name of your model on the Hugging Face Hub
+model_name = "Alexander27/Nano-Butterfly"
+
+# 2. Load the tokenizer and model
+print(f"Loading model: {model_name}")
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+print("Model loaded successfully!")
+
+# 3. Define the prompt (the input text for the model)
+prompt = "The future of artificial intelligence is "
+
+# 4. Prepare the input for the model
+input_ids = tokenizer.encode(prompt, return_tensors="pt")
+
+# 5. Generate text
+# max_length controls how long the output will be
+output_sequences = model.generate(
+    input_ids=input_ids,
+    max_length=100,
+    num_return_sequences=1
+)
 
-Contributing
+# 6. Decode the output and print it
+generated_text = tokenizer.decode(output_sequences[0], skip_special_tokens=True)
 
-Contributions are welcome! Please fork the repository, make your changes, and submit a pull request. All contributions must follow the code style of the project.
+print("\n--- Model Output ---")
+print(generated_text)