Fill-Mask
Transformers
Safetensors
English
bert
protein
protbert
masked-language-modeling
bioinformatics
sequence-prediction
Instructions to use faceless-void/protbert-sequence-unmasking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use faceless-void/protbert-sequence-unmasking with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="faceless-void/protbert-sequence-unmasking")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("faceless-void/protbert-sequence-unmasking") model = AutoModelForMaskedLM.from_pretrained("faceless-void/protbert-sequence-unmasking", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download generation_config.json from faceless-void/protbert-sequence-unmasking: direct link, hf CLI and curl.
- Browser
- Download file 90 Bytes
-
https://huggingface.co/faceless-void/protbert-sequence-unmasking/resolve/main/generation_config.json
- Command line
-
hf download hf://faceless-void/protbert-sequence-unmasking/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/faceless-void/protbert-sequence-unmasking/resolve/main/generation_config.json
90 Bytes
| { | |
| "_from_model_config": true, | |
| "pad_token_id": 0, | |
| "transformers_version": "4.41.1" | |
| } | |