Instructions to use finiteautomata/bertweet-base-sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use finiteautomata/bertweet-base-sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="finiteautomata/bertweet-base-sentiment-analysis")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("finiteautomata/bertweet-base-sentiment-analysis") model = AutoModelForSequenceClassification.from_pretrained("finiteautomata/bertweet-base-sentiment-analysis", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from finiteautomata/bertweet-base-sentiment-analysis: direct link, hf CLI and curl.
- Browser
- Download file 540 MB
-
https://huggingface.co/finiteautomata/bertweet-base-sentiment-analysis/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://finiteautomata/bertweet-base-sentiment-analysis/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/finiteautomata/bertweet-base-sentiment-analysis/resolve/main/pytorch_model.bin
540 MB
- Xet hash:
- 951d4d6651ba17b7888bd8b3a0b44fc19ab95ce91ac9140d0c4b9f7a85df0b0c
- Size of remote file:
- 540 MB
- SHA256:
- a481474183bf0ca80b485cd8d8dd5f0811fcce3c5ecef84c3ca180ed54918771
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