Update README.md

README.md

@@ -1,3 +1,20 @@
+---
+language:
+- en
+license: apache-2.0
+base_model: HuggingFaceTB/SmolLM2-135M-Instruct
+tags:
+- llm
+- fine-tuned
+- lora
+- sft
+- text-generation
+- student-project
+datasets:
+- HuggingFaceTB/smoltalk
+pipeline_tag: text-generation
+---
+
 # chatOP — SmolLM2-135M Fine-tuned
 
 A fine-tuned version of [SmolLM2-135M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct) trained to act as a friendly study assistant for CS and ML concepts.
@@ -46,42 +63,6 @@ A fine-tuned version of [SmolLM2-135M-Instruct](https://huggingface.co/HuggingFa
 - **GPU:** NVIDIA Tesla T4 (Google Colab)
 - **Training time:** ~15–20 minutes
 
-## Usage
-
-```python
-from transformers import AutoModelForCausalLM, AutoTokenizer
-import torch
-
-model = AutoModelForCausalLM.from_pretrained("your-username/study-buddy")
-tokenizer = AutoTokenizer.from_pretrained("your-username/study-buddy")
-
-messages = [
-    {"role": "user", "content": "What is backpropagation?"}
-]
-
-text = tokenizer.apply_chat_template(
-    messages,
-    tokenize=False,
-    add_generation_prompt=True
-)
-inputs = tokenizer(text, return_tensors="pt")
-
-with torch.no_grad():
-    output = model.generate(
-        **inputs,
-        max_new_tokens=200,
-        temperature=0.7,
-        do_sample=True,
-        pad_token_id=tokenizer.eos_token_id
-    )
-
-response = tokenizer.decode(
-    output[0][inputs["input_ids"].shape[1]:],
-    skip_special_tokens=True
-)
-print(response)
-```
-
 ## Example Outputs
 
 **Prompt:** What is machine learning?