Instructions to use jambo/microsoftBio-renet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jambo/microsoftBio-renet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jambo/microsoftBio-renet")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jambo/microsoftBio-renet") model = AutoModelForSequenceClassification.from_pretrained("jambo/microsoftBio-renet", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jambo/microsoftBio-renet: direct link, hf CLI and curl.
- Browser
- Download file 2.8 kB
-
https://huggingface.co/jambo/microsoftBio-renet/resolve/refs%2Fpr%2F2/training_args.bin
- Command line
-
hf download hf://jambo/microsoftBio-renet@refs/pr/2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jambo/microsoftBio-renet/resolve/refs%2Fpr%2F2/training_args.bin
2.8 kB
- Xet hash:
- e786adf05f50146117075c8f83b645e8d9a71ef6e07e9d4b904081fe3019f2aa
- Size of remote file:
- 2.8 kB
- SHA256:
- eab8d3c58121f92df787a314cf32b20b197226cd459298bd7de47388c1168dfc
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