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README.md

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+---
+license: apache-2.0
+language:
+- en
+tags:
+- gguf
+- ollama
+- fda
+- regulatory
+- task-extraction
+- llama
+datasets:
+- fda-documents
+pipeline_tag: text-generation
+model_type: llama
+quantization: Q8_0
+---
+
+# FDA Task Classifier - GGUF
+
+A specialized language model fine-tuned for extracting regulatory tasks from FDA correspondence documents.
+
+## Model Details
+
+- **Model Type:** LlamaForCausalLM
+- **Parameters:** 361.82M
+- **Quantization:** Q8_0 GGUF
+- **Context Window:** 4096 tokens
+- **File Size:** 369 MB
+- **License:** Apache 2.0
+
+## Quick Start with Ollama
+
+The easiest way to use this model is with [Ollama](https://ollama.com):
+
+```bash
+# Pull the Modelfile from this repo
+wget https://huggingface.co/llama-farm/fda-task-classifier-gguf/raw/main/Modelfile
+
+# Create the model in Ollama
+ollama create fda-task-classifier -f Modelfile
+
+# Run the model
+ollama run fda-task-classifier
+```
+
+### Or download manually:
+
+```bash
+# Download the GGUF file
+wget https://huggingface.co/llama-farm/fda-task-classifier-gguf/resolve/main/model.gguf
+
+# Create a Modelfile
+cat > Modelfile << 'EOF'
+FROM ./model.gguf
+
+PARAMETER temperature 0.3
+PARAMETER top_p 0.9
+PARAMETER top_k 40
+PARAMETER num_ctx 4096
+PARAMETER num_predict 512
+
+SYSTEM """You are an FDA regulatory task extraction specialist. Your role is to analyze document chunks and identify specific FDA regulatory tasks, requirements, and action items.
+
+When analyzing text, focus on:
+- Regulatory submissions and deadlines
+- Clinical trial requirements
+- Manufacturing and quality control tasks
+- Compliance and reporting obligations
+- Safety monitoring requirements
+- Documentation and record-keeping tasks
+
+Extract tasks in a structured format with:
+- Task description
+- Regulatory category (e.g., clinical, manufacturing, compliance)
+- Priority level if mentioned
+- Deadline if specified
+- Relevant FDA regulation references
+
+Be precise and factual. Only extract tasks that are explicitly stated or clearly implied in the text."""
+EOF
+
+# Create model in Ollama
+ollama create fda-task-classifier -f Modelfile
+```
+
+## Usage Examples
+
+### Simple Task Extraction
+
+```bash
+ollama run fda-task-classifier "Extract all FDA regulatory tasks from this text:
+
+The sponsor must submit a complete Chemistry, Manufacturing, and Controls (CMC)
+section as part of the IND application within 30 days of this notice. Additionally,
+the clinical protocol must be amended to include enhanced safety monitoring procedures."
+```
+
+**Output:**
+```
+1. Submit complete CMC section within 30 days
+   Category: Manufacturing/Submission
+   Priority: Critical
+   Deadline: 30 days from notice
+
+2. Amend clinical protocol to include enhanced safety monitoring
+   Category: Clinical/Safety
+   Priority: High
+```
+
+### API Usage
+
+```python
+import requests
+
+response = requests.post('http://localhost:11434/api/generate', json={
+    "model": "fda-task-classifier",
+    "prompt": "Extract tasks from: The sponsor should provide updated stability data...",
+    "stream": False
+})
+
+print(response.json()['response'])
+```
+
+## Model Specialization
+
+This model is specifically trained to identify:
+
+✅ **Submission Requirements**
+- IND/NDA submissions
+- Supplemental applications
+- Annual reports
+
+✅ **Clinical Trial Directives**
+- Protocol amendments
+- Safety monitoring
+- Patient enrollment criteria
+
+✅ **Manufacturing Tasks**
+- CMC requirements
+- Quality control procedures
+- GMP compliance
+
+✅ **Regulatory Compliance**
+- 21 CFR citations
+- Inspection responses
+- CAPA plans
+
+✅ **Safety Obligations**
+- Adverse event reporting
+- REMS requirements
+- Risk assessments
+
+## Integration with LlamaFarm
+
+This model is designed to work seamlessly with [LlamaFarm](https://github.com/llama-farm/llamafarm):
+
+```yaml
+# llamafarm.yaml
+runtime:
+  models:
+    - name: fda-task-classifier
+      provider: ollama
+      model: fda-task-classifier
+      base_url: http://localhost:11434/v1
+
+agents:
+  - name: fda_document_analyzer
+    type: document_analyzer
+    model: fda-task-classifier
+    description: Extracts FDA regulatory tasks from documents
+```
+
+## Performance
+
+- **Speed:** ~2-3 seconds per document chunk on M1 Mac
+- **Accuracy:** Optimized for FDA regulatory language
+- **Context:** 4096 tokens (sufficient for most FDA letter sections)
+- **Memory:** ~500MB RAM usage
+
+## Files in This Repository
+
+- `model.gguf` - Quantized model weights (Q8_0)
+- `Modelfile` - Ollama model configuration
+- `README.md` - Original documentation
+- `USAGE.md` - Detailed usage examples
+- `model_info.json` - Model metadata
+
+## Technical Details
+
+**Architecture:** LlamaForCausalLM
+**Quantization:** Q8_0 (8-bit quantization)
+**Base Model:** [Undisclosed]
+**Training Data:** FDA correspondence, deficiency letters, meeting minutes
+
+**Recommended Parameters:**
+- `temperature: 0.3` - More deterministic outputs
+- `top_p: 0.9` - Focused sampling
+- `num_ctx: 4096` - Optimized context window
+- `num_predict: 512` - Concise task lists
+
+## Use Cases
+
+1. **Regulatory Document Processing**
+   - Extract action items from FDA deficiency letters
+   - Identify compliance obligations
+   - Track submission deadlines
+
+2. **Quality Assurance**
+   - Parse inspection observations (483s)
+   - Extract CAPA requirements
+   - Identify GMP violations
+
+3. **Clinical Operations**
+   - Extract protocol amendment requirements
+   - Identify safety reporting obligations
+   - Track clinical trial milestones
+
+4. **Automated Compliance**
+   - Build task tracking systems
+   - Create regulatory calendars
+   - Generate compliance reports
+
+## Limitations
+
+- Optimized for FDA documents (US regulatory text)
+- May not generalize well to other regulatory bodies (EMA, PMDA)
+- Works best with formal regulatory correspondence
+- Limited to English language
+
+## Citation
+
+If you use this model in your research or application, please cite:
+
+```bibtex
+@software{fda_task_classifier_2025,
+  title={FDA Task Classifier GGUF},
+  author={LlamaFarm Team},
+  year={2025},
+  url={https://huggingface.co/llama-farm/fda-task-classifier-gguf}
+}
+```
+
+## License
+
+Apache 2.0 - See LICENSE file for details
+
+## Links
+
+- **LlamaFarm:** https://github.com/llama-farm/llamafarm
+- **Ollama:** https://ollama.com
+- **Issues:** https://github.com/llama-farm/llamafarm/issues
+- **Discord:** https://discord.gg/RrAUXTCVNF