Instructions to use mgh6/TCS_MLM_SaProt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mgh6/TCS_MLM_SaProt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mgh6/TCS_MLM_SaProt")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mgh6/TCS_MLM_SaProt") model = AutoModelForMaskedLM.from_pretrained("mgh6/TCS_MLM_SaProt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download adapter_config.json from mgh6/TCS_MLM_SaProt: direct link, hf CLI and curl.
- Browser
- Download file 692 Bytes
-
https://huggingface.co/mgh6/TCS_MLM_SaProt/resolve/5d2affef4c81b7f43715c84ee06830e80098b7e4/adapter_config.json
- Command line
-
hf download hf://mgh6/TCS_MLM_SaProt@5d2affef4c81b7f43715c84ee06830e80098b7e4/adapter_config.json
-
curl -L -o adapter_config.json https://huggingface.co/mgh6/TCS_MLM_SaProt/resolve/5d2affef4c81b7f43715c84ee06830e80098b7e4/adapter_config.json
692 Bytes
| { | |
| "alpha_pattern": {}, | |
| "auto_mapping": null, | |
| "base_model_name_or_path": "westlake-repl/SaProt_650M_PDB", | |
| "bias": "none", | |
| "fan_in_fan_out": false, | |
| "inference_mode": true, | |
| "init_lora_weights": true, | |
| "layer_replication": null, | |
| "layers_pattern": null, | |
| "layers_to_transform": null, | |
| "loftq_config": {}, | |
| "lora_alpha": 8, | |
| "lora_dropout": 0.1, | |
| "megatron_config": null, | |
| "megatron_core": "megatron.core", | |
| "modules_to_save": [ | |
| "classifier", | |
| "score" | |
| ], | |
| "peft_type": "LORA", | |
| "r": 8, | |
| "rank_pattern": {}, | |
| "revision": null, | |
| "target_modules": [ | |
| "value", | |
| "key", | |
| "query" | |
| ], | |
| "task_type": "TOKEN_CLS", | |
| "use_dora": false, | |
| "use_rslora": false | |
| } |