Text Classification
Transformers
Safetensors
English
Portuguese
roberta
biology
science
nlp
biomedical
filter
medical
text-embeddings-inference
Instructions to use Madras1/RobertaBioClass with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Madras1/RobertaBioClass with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Madras1/RobertaBioClass")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Madras1/RobertaBioClass") model = AutoModelForSequenceClassification.from_pretrained("Madras1/RobertaBioClass", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download rng_state.pth from Madras1/RobertaBioClass: direct link, hf CLI and curl.
- Browser
- Download file 14.6 kB
-
https://huggingface.co/Madras1/RobertaBioClass/resolve/main/rng_state.pth
- Command line
-
hf download hf://Madras1/RobertaBioClass/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/Madras1/RobertaBioClass/resolve/main/rng_state.pth
14.6 kB
- Xet hash:
- fe24e89308515c96ea4273c5f5497f574e9532641f2f3d801d8f8a473bdf9221
- Size of remote file:
- 14.6 kB
- SHA256:
- e0eb35c4d8c39e70c22734a402379479ad9d31c632fc4320d47496037717dc79
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