Instructions to use xeventminer/roberta-large-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xeventminer/roberta-large-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xeventminer/roberta-large-en")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xeventminer/roberta-large-en") model = AutoModelForSequenceClassification.from_pretrained("xeventminer/roberta-large-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from xeventminer/roberta-large-en: direct link, hf CLI and curl.
- Browser
- Download file 2.84 GB
-
https://huggingface.co/xeventminer/roberta-large-en/resolve/main/optimizer.pt
- Command line
-
hf download hf://xeventminer/roberta-large-en/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/xeventminer/roberta-large-en/resolve/main/optimizer.pt
2.84 GB
- Xet hash:
- e8e56a50731de29f26619f845bfff53b5c1e0dd24de60bc7ae1f7e903183f17e
- Size of remote file:
- 2.84 GB
- SHA256:
- 9960d0002adb5aa7581e44c66b0a76f30fb78e948c05815e0e77fc6894917ad9
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