Instructions to use nzindoc/study-dictionary-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nzindoc/study-dictionary-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nzindoc/study-dictionary-roberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nzindoc/study-dictionary-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("nzindoc/study-dictionary-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from nzindoc/study-dictionary-roberta-base: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/nzindoc/study-dictionary-roberta-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://nzindoc/study-dictionary-roberta-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nzindoc/study-dictionary-roberta-base/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 579c7477c65abb005bf5b7a6e51f23438196966fd35dbe5d8b445236f94db042
- Size of remote file:
- 499 MB
- SHA256:
- daa9a8d1e126d806961f971eba10fa984e160257c46dfac82666a4aa7adc2d58
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