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
File size: 448 Bytes
117e99b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"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"
}
|