Add model card

README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen3-2B-Instruct
+tags:
+- qwen3
+- text-generation
+- peft
+- lora
+- trl
+- sft
+- smiles
+library_name: transformers
+---
+
+# Qwens_SFT
+
+This repository contains a model artifact fine-tuned from `Qwen/Qwen3-2B-Instruct`.
+
+The model was trained to take a SMILES string and generate JSON with:
+
+- `failure_summary_for_editing`
+- `failure_properties`
+- `failure_properties_display`
+- `editing_directions`
+
+Training data source: `/home/onkarks2/transformers/fallen_angel_with_properties.csv`
+
+## Example Prompt
+
+```text
+Given the SMILES string below, generate the clinical failure editing information.
+
+SMILES: Cc1cc(C)c(N)c(n1)C#Cc1cccc(F)c1
+
+Return valid JSON with exactly these keys:
+- "failure_summary_for_editing"
+- "failure_properties"
+- "failure_properties_display"
+- "editing_directions"
+```
+
+## Loading A LoRA Adapter
+
+```python
+from peft import PeftModel
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+base_model = "Qwen/Qwen3-2B-Instruct"
+adapter_id = "onkarsus13/Qwens_SFT"
+
+tokenizer = AutoTokenizer.from_pretrained(adapter_id)
+model = AutoModelForCausalLM.from_pretrained(base_model, torch_dtype="auto", device_map="auto")
+model = PeftModel.from_pretrained(model, adapter_id)
+```