Feature Extraction
Transformers
Safetensors
seqscreen
proteins
molecules
bioinformatics
drug-discovery
custom_code
Instructions to use SaeedLab/SeqScreen-Finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SaeedLab/SeqScreen-Finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SaeedLab/SeqScreen-Finetuning", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SaeedLab/SeqScreen-Finetuning", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "SeqScreenModel" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_seqscreen.SeqScreenConfig", | |
| "AutoModel": "modeling_seqscreen.SeqScreenModel" | |
| }, | |
| "dropout": 0.1, | |
| "dtype": "float32", | |
| "esm2_model_name": "facebook/esm2_t36_3B_UR50D", | |
| "lora_adapter_repo": "SaeedLab/SeqScreen-lora", | |
| "model_type": "seqscreen", | |
| "mol_dim": 768, | |
| "proj_dim": 512, | |
| "prot_dim": 2560, | |
| "transformers_version": "4.57.3" | |
| } | |