Instructions to use rti-international/rota with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rti-international/rota with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rti-international/rota")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rti-international/rota") model = AutoModelForSequenceClassification.from_pretrained("rti-international/rota", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from rti-international/rota: direct link, hf CLI and curl.
- Browser
- Download file 329 MB
-
https://huggingface.co/rti-international/rota/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://rti-international/rota/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/rti-international/rota/resolve/main/flax_model.msgpack
329 MB
- Xet hash:
- e2d20479eaf69c15a616cb8cac1301e6a45462af64d8fddf00b930f75a0d4299
- Size of remote file:
- 329 MB
- SHA256:
- 11ce261f74d7b8b90a0efb019f1f1bbc7c569521d519665795c8b510c181eece
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