Instructions to use InstaDeepAI/nucleotide-transformer-500m-human-ref with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InstaDeepAI/nucleotide-transformer-500m-human-ref with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="InstaDeepAI/nucleotide-transformer-500m-human-ref")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("InstaDeepAI/nucleotide-transformer-500m-human-ref") model = AutoModelForMaskedLM.from_pretrained("InstaDeepAI/nucleotide-transformer-500m-human-ref", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from InstaDeepAI/nucleotide-transformer-500m-human-ref: direct link, hf CLI and curl.
- Browser
- Download file 129 Bytes
-
https://huggingface.co/InstaDeepAI/nucleotide-transformer-500m-human-ref/resolve/28d7fac71fc0a20d83713d8fb4a520964a7913b7/tokenizer_config.json
- Command line
-
hf download hf://InstaDeepAI/nucleotide-transformer-500m-human-ref@28d7fac71fc0a20d83713d8fb4a520964a7913b7/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/InstaDeepAI/nucleotide-transformer-500m-human-ref/resolve/28d7fac71fc0a20d83713d8fb4a520964a7913b7/tokenizer_config.json
129 Bytes
| { | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": null, | |
| "model_max_length": 1000, | |
| "tokenizer_class": "EsmTokenizer" | |
| } | |