Revert: remove 'How to use' section from README.md per user request.

README.md

@@ -10,114 +10,49 @@ language:
 base_model: LiquidAI/LFM2-1.2B
 pipeline_tag: text-generation
 ---
-#
- lfm2-1.2b-sermon-instruct-qlora
-**
-Author
-**
-: Delight Aheebwa
-  
-**
-Contact
-**
-: Please contact via Hugging Face or GitHub profile (delight2004)
-##
- Model Overview
--
- 
-**
-Type
-**
-: Causal Language Model (LM)
--
- 
-**
-Base Model
-**
-: LiquidAI/LFM2-1.2B
--
- 
-**
-Fine-tuning technique
-**
-: QLoRA with PEFT (LoRA adapters)
--
- 
-**
-Language(s)
-**
-: English only
--
- 
-**
-Intended Use
-**
-: Research, educational, and sermon content generation on Christian and theological topics (especially inspired by John Piper's teachings).
--
- 
-**
-Tags
-**
-: Uganda, theology, Christianity
--
- 
-**
-License
-**
-: OpenRAIL Non-Commercial Variant
-##
- Dataset & Training
--
- 
-**
-Data source
-**
-: Transcripts of YouTube sermons by John Piper (excluding "Ask Pastor John" podcast transcripts)
--
- 
-**
-Filtered dataset size
-**
-: 165 entries after filtering (~10% set aside for validation)
--
- 
-**
-Preprocessing
-**
-: Splitting and curation as 
-[
-detailed in the training notebook
-]
-(
-https://colab.research.google.com/drive/1pU7TQfneS48j8XxWjM1DPesUao5GEtIs#scrollTo=Wj07AZOhCnxl
-)
--
- 
-**
-Training details
-**
-:
-    
--
- Hardware: Google Colab free tier (T4 GPU)
-    
--
- epochs: 4
-    
--
- batch size: 1 (gradient_accumulation_steps=4)
-    
--
- learning rate: 2e-5
+# lfm2-1.2b-sermon-instruct-qlora
 
-## How to use
+**Author**: Delight Aheebwa  
+**Contact**: Please contact via Hugging Face or GitHub profile (delight2004)
 
-```python
-from transformers import pipeline
+## Model Overview
+- **Type**: Causal Language Model (LM)
+- **Base Model**: LiquidAI/LFM2-1.2B
+- **Fine-tuning technique**: QLoRA with PEFT (LoRA adapters)
+- **Language(s)**: English only
+- **Intended Use**: Research, educational, and sermon content generation on Christian and theological topics (especially inspired by John Piper's teachings).
+- **Tags**: Uganda, theology, Christianity
+- **License**: OpenRAIL Non-Commercial Variant
 
-# Anyone can now load your model by its name!
-pipe = pipeline("text-generation", model="delight2004/lfm2-1.2b-sermon-instruct-qlora")
+## Dataset & Training
+- **Data source**: Transcripts of YouTube sermons by John Piper (excluding "Ask Pastor John" podcast transcripts)
+- **Filtered dataset size**: 165 entries after filtering (~10% set aside for validation)
+- **Preprocessing**: Splitting and curation as [detailed in the training notebook](https://colab.research.google.com/drive/1pU7TQfneS48j8XxWjM1DPesUao5GEtIs#scrollTo=Wj07AZOhCnxl)
+- **Training details**:
+    - Hardware: Google Colab free tier (T4 GPU)
+    - epochs: 4
+    - batch size: 1 (gradient_accumulation_steps=4)
+    - learning rate: 2e-5
+    - sequence length: 512
+    - quantization: 4-bit (bnb_4bit_quant_type="nf4", bnb_4bit_compute_dtype=torch.bfloat16)
+    - Only LoRA adapter params were trained (~0.05% of total)
+    - Full trainer/config code: see Colab notebook above
 
-result = pipe("Preach a short sermon in the style of John Piper on the topic of: 'Grace'")
-print(result[0]['generated_text'])
-```
+## Evaluation
+- No formal evaluation/benchmarking was conducted. Use at your own discretion – feedback and community tests are welcome.
+
+## Limitations & Disclaimer
+- Not intended for production or commercial use.
+- Outputs should not be treated as official theological advice.
+- Possible biases and limitations inherited from the dataset/model base – may reflect the original preacher's views.
+- Model may hallucinate or generate plausible but incorrect theological claims or references.
+
+## Technical
+- **Architecture**: Causal Transformer (1.2B params, LiquidAI flavor)
+- **Adapter config**: PEFT/QLoRA
+- **Training framework**: Hugging Face Transformers, TRL, PEFT, bitsandbytes, PyTorch
+- **Compute**: Google Colab T4 (free tier, single GPU)
+- **Notebook**: [john_piper.ipynb](https://colab.research.google.com/drive/1pU7TQfneS48j8XxWjM1DPesUao5GEtIs#scrollTo=Wj07AZOhCnxl)
+
+## Citation
+If you use this model, please cite it or reference its Hugging Face page, and acknowledge John Piper's YouTube sermons as the data source.