Update README.md

README.md

@@ -7,4 +7,36 @@ language:
 base_model:
 - facebook/opt-350m
 new_version: sweatSmile/marx-opt350m-finetuned-v1
----
+---
+
+## 🧠 Model: marx-opt350m-finetuned-v1
+
+This is a fine-tuned version of [`facebook/opt-350m`](https://huggingface.co/facebook/opt-350m) on the [`sweatSmile/marx-dataset`](https://huggingface.co/datasets/sweatSmile/marx-dataset) — a conversational dataset consisting of question-answer dialogues about Marxist theory, history, and related political contexts.
+
+The model is optimized for **dialogue-style QA** on political/philosophical topics.
+
+---
+
+## 📊 Training Details
+
+- **Base model**: facebook/opt-350m
+- **Dataset**: sweatSmile/marx-dataset
+- **Epochs**: 5
+- **Trainer**: TRL's `SFTTrainer` from `trl`
+- **Loss**: Reduced steadily to ~0.36
+- **ROUGE-L**: ~0.53 on evaluation set
+
+---
+
+## 🔍 Example Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("sweatSmile/marx-opt350m-finetuned-v1")
+tokenizer = AutoTokenizer.from_pretrained("sweatSmile/marx-opt350m-finetuned-v1")
+
+prompt = "### Human: Who were commissioned to prepare the party programme for the Communist League?\n### Assistant:"
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_length=100)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))