Instructions to use Jedida/sentence_sentiments_analysis_roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jedida/sentence_sentiments_analysis_roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jedida/sentence_sentiments_analysis_roberta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jedida/sentence_sentiments_analysis_roberta") model = AutoModelForSequenceClassification.from_pretrained("Jedida/sentence_sentiments_analysis_roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Jedida/sentence_sentiments_analysis_roberta: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/Jedida/sentence_sentiments_analysis_roberta/resolve/main/training_args.bin
- Command line
-
hf download hf://Jedida/sentence_sentiments_analysis_roberta/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/Jedida/sentence_sentiments_analysis_roberta/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- 5c4fad1406b14458fd1377f8987f3be586fc602569bdfcf17d5ef44971c7d53c
- Size of remote file:
- 4.09 kB
- SHA256:
- 30d80b8dd729a7e3cb148da85b9ddf758a680d7c89901c0ebda0aba4c0916931
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