Text Classification
Transformers
Safetensors
PyTorch
English
esm
bioinformatics
protein
protein-variant
genomics
cancer
esm2
sequence-classification
fastapi
Eval Results (legacy)
Instructions to use RizFie/Eleuthia-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RizFie/Eleuthia-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RizFie/Eleuthia-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RizFie/Eleuthia-v1") model = AutoModelForSequenceClassification.from_pretrained("RizFie/Eleuthia-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e1bc6e2fe06bfb6dbb0a6cdcbad4fc67ba0b95e1916a9331a545c1d5259bae22
- Size of remote file:
- 5.2 kB
- SHA256:
- 41dcd348625d7560181e1e3584702fe7c240a89854ee7b9d796d14f10a0a6d01
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.