Instructions to use tanoManzo/nucleotide-transformer-500m-human-ref_ft_BioS2_1kbpHG19_DHSs_H3K27AC_one_shot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tanoManzo/nucleotide-transformer-500m-human-ref_ft_BioS2_1kbpHG19_DHSs_H3K27AC_one_shot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tanoManzo/nucleotide-transformer-500m-human-ref_ft_BioS2_1kbpHG19_DHSs_H3K27AC_one_shot")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tanoManzo/nucleotide-transformer-500m-human-ref_ft_BioS2_1kbpHG19_DHSs_H3K27AC_one_shot") model = AutoModelForSequenceClassification.from_pretrained("tanoManzo/nucleotide-transformer-500m-human-ref_ft_BioS2_1kbpHG19_DHSs_H3K27AC_one_shot", device_map="auto") - Notebooks
- Google Colab
- Kaggle
nucleotide-transformer-500m-human-ref_ft_BioS2_1kbpHG19_DHSs_H3K27AC_one_shot / tokenizer_config.json
Download tokenizer_config.json from tanoManzo/nucleotide-transformer-500m-human-ref_ft_BioS2_1kbpHG19_DHSs_H3K27AC_one_shot: direct link, hf CLI and curl.
- Browser
- Download file 928 Bytes
-
https://huggingface.co/tanoManzo/nucleotide-transformer-500m-human-ref_ft_BioS2_1kbpHG19_DHSs_H3K27AC_one_shot/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://tanoManzo/nucleotide-transformer-500m-human-ref_ft_BioS2_1kbpHG19_DHSs_H3K27AC_one_shot/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/tanoManzo/nucleotide-transformer-500m-human-ref_ft_BioS2_1kbpHG19_DHSs_H3K27AC_one_shot/resolve/main/tokenizer_config.json
928 Bytes
| { | |
| "added_tokens_decoder": { | |
| "0": { | |
| "content": "<unk>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "1": { | |
| "content": "<pad>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "2": { | |
| "content": "<mask>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "3": { | |
| "content": "<cls>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| } | |
| }, | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "<cls>", | |
| "eos_token": null, | |
| "mask_token": "<mask>", | |
| "model_max_length": 1000, | |
| "pad_token": "<pad>", | |
| "tokenizer_class": "EsmTokenizer", | |
| "unk_token": "<unk>" | |
| } | |