Instructions to use Jedida/sentence_sentiments_analysis_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jedida/sentence_sentiments_analysis_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jedida/sentence_sentiments_analysis_bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jedida/sentence_sentiments_analysis_bert") model = AutoModelForSequenceClassification.from_pretrained("Jedida/sentence_sentiments_analysis_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Jedida/sentence_sentiments_analysis_bert: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/Jedida/sentence_sentiments_analysis_bert/resolve/main/training_args.bin
- Command line
-
hf download hf://Jedida/sentence_sentiments_analysis_bert/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/Jedida/sentence_sentiments_analysis_bert/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- c9c8387d217613ef8c317f783028fabf19da33da9921cf94a516e9ce60fd1e8f
- Size of remote file:
- 4.09 kB
- SHA256:
- 3f7587df29a9909b6e051f79ce7a47726c8da1d4c59cbeac69264ab983a7dda6
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