Update ML Intern artifact metadata

README.md

@@ -10,6 +10,7 @@ tags:
 - intent-based-networking
 - network-slicing
 - rtx-6000-ada
+- ml-intern
 base_model:
 - Qwen/Qwen3-8B
 datasets:
@@ -287,3 +288,23 @@ requirements.txt
 - TRL SFTTrainer docs: https://huggingface.co/docs/trl/sft_trainer
 - TRL PEFT integration: https://huggingface.co/docs/trl/peft_integration
 - Source dataset: https://huggingface.co/datasets/nraptisss/TMF921-intent-to-config-research-sota
+
+<!-- ml-intern-provenance -->
+## Generated by ML Intern
+
+This model repository was generated by [ML Intern](https://github.com/huggingface/ml-intern), an agent for machine learning research and development on the Hugging Face Hub.
+
+- Try ML Intern: https://smolagents-ml-intern.hf.space
+- Source code: https://github.com/huggingface/ml-intern
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = 'nraptisss/tmf921-intent-training'
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id)
+```
+
+For non-causal architectures, replace `AutoModelForCausalLM` with the appropriate `AutoModel` class.