Instructions to use A-Funakoshi/bert-multilingual-sentiments-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use A-Funakoshi/bert-multilingual-sentiments-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="A-Funakoshi/bert-multilingual-sentiments-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("A-Funakoshi/bert-multilingual-sentiments-base") model = AutoModelForSequenceClassification.from_pretrained("A-Funakoshi/bert-multilingual-sentiments-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from A-Funakoshi/bert-multilingual-sentiments-base: direct link, hf CLI and curl.
- Browser
- Download file 443 MB
-
https://huggingface.co/A-Funakoshi/bert-multilingual-sentiments-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://A-Funakoshi/bert-multilingual-sentiments-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/A-Funakoshi/bert-multilingual-sentiments-base/resolve/main/pytorch_model.bin
443 MB
- Xet hash:
- 3ac0e6f5614bf30978d19952ed7f2b7a9b99a2b91f707d3e32c370a81ad05a77
- Size of remote file:
- 443 MB
- SHA256:
- 093bf6114a2b698ac241356bf234a1f418db0c98b78472b00ff63ba536ca7a73
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