Text Classification
Transformers
Safetensors
English
bert
DNA
genomics
fish
sequence-classification
FishNALM
fine-tuned
promoter-300-tata
Instructions to use bioinfoihb/FishNALM-20L_prom_300_tata with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bioinfoihb/FishNALM-20L_prom_300_tata with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bioinfoihb/FishNALM-20L_prom_300_tata")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bioinfoihb/FishNALM-20L_prom_300_tata") model = AutoModelForSequenceClassification.from_pretrained("bioinfoihb/FishNALM-20L_prom_300_tata", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 557 Bytes
8038acf | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | {
"cls_token": {
"content": "<cls>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
},
"mask_token": {
"content": "<mask>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
},
"pad_token": {
"content": "<pad>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
},
"unk_token": {
"content": "<unk>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
}
}
|