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
- Xet hash:
- cd81520cd9e5eb78abddd2699d609fa21a5a41c5cf4c6610c3204e99d5e62930
- Size of remote file:
- 1.24 GB
- SHA256:
- 480430c07f4e82ac02f733b801ef2438d4026621f1e34a2097a386e7a866e7ea
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