| === Upload Instructions === | |
| 1. Navigate to the upload directory: | |
| cd flowamp_upload_small | |
| 2. Initialize git repository: | |
| git init | |
| git add . | |
| git commit -m "Initial FlowAMP upload (small version)" | |
| 3. Add Hugging Face remote: | |
| git remote add origin https://huggingface.co/esunAI/FlowAMP | |
| 4. Push to Hugging Face: | |
| git push -u origin main | |
| === Files Included === | |
| Core Model: | |
| - final_flow_model.py: Main FlowAMP model architecture | |
| - final_sequence_encoder.py: ESM-2 sequence encoding | |
| - final_sequence_decoder.py: Sequence decoding and generation | |
| - compressor_with_embeddings.py: Embedding compression/decompression | |
| - cfg_dataset.py: CFG dataset and dataloader | |
| Training: | |
| - amp_flow_training_single_gpu_full_data.py: Single GPU training | |
| - amp_flow_training_multi_gpu.py: Multi-GPU training | |
| - launch_*.sh: Training launch scripts | |
| Models: | |
| - normalization_stats.pt: Preprocessing statistics | |
| - MODEL_FILES_INFO.md: Information about missing large model files | |
| Apex Integration: | |
| - apex/AMP_DL_model_twohead.py: Apex model architecture | |
| - apex/predict.py: MIC prediction script | |
| Documentation: | |
| - README.md: Comprehensive project documentation | |
| - model_card.md: Hugging Face model card | |
| - usage_example.py: Usage demonstration | |
| - requirements.txt: Python dependencies | |
| === Note === | |
| This is a smaller version without large model files due to Hugging Face size limits. | |
| See MODEL_FILES_INFO.md for details on obtaining model weights. | |