Update README.md

README.md

@@ -1,3 +1,52 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+base_model:
+- google/flan-t5-small
+pipeline_tag: text2text-generation
+---
+# dafilab/chat-title-generator
+
+Fine-tuned `flan-t5-small` model for generating short titles from chats.
+
+## Model Details
+
+- **Base model**: google/flan-t5-small  
+- **Training examples**: 10,000  
+- **Epochs**: 2  
+- **Final training loss**: 0.778800  
+- **Train batch size per device**: 4  
+- **Total optimization steps**: 500  
+
+## Usage
+
+```python
+from transformers import T5ForConditionalGeneration, T5Tokenizer
+
+model = T5ForConditionalGeneration.from_pretrained("dafilab/chat-title-generator")
+tokenizer = T5Tokenizer.from_pretrained("dafilab/chat-title-generator", legacy=False)
+
+def generate_chat_title(text):
+    input_text = "short title: " + text
+    inputs = tokenizer(input_text, return_tensors="pt", truncation=True, max_length=512)
+    outputs = model.generate(
+        input_ids=inputs.input_ids,
+        max_length=64,
+        num_beams=4,
+        early_stopping=True,
+        pad_token_id=tokenizer.pad_token_id,
+        eos_token_id=tokenizer.eos_token_id
+    )
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+text = """How can I access the GPU of my other computer remotely for ML training?
+To access your other computer's GPU remotely for machine learning (ML) training,
+you need to set up remote access to the machine and ensure that it can properly leverage the GPU for computations.
+There are several ways to do this, depending on your operating system and the tools you prefer to use."""
+print(generate_chat_title(text))
+
+```
+
+## Output
+```
+Remote GPU Access
+```