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