Instructions to use tr3cks/2LabelsSentimentAnalysisSpanish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tr3cks/2LabelsSentimentAnalysisSpanish with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tr3cks/2LabelsSentimentAnalysisSpanish")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tr3cks/2LabelsSentimentAnalysisSpanish") model = AutoModelForSequenceClassification.from_pretrained("tr3cks/2LabelsSentimentAnalysisSpanish", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from tr3cks/2LabelsSentimentAnalysisSpanish: direct link, hf CLI and curl.
- Browser
- Download file 439 MB
-
https://huggingface.co/tr3cks/2LabelsSentimentAnalysisSpanish/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://tr3cks/2LabelsSentimentAnalysisSpanish/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/tr3cks/2LabelsSentimentAnalysisSpanish/resolve/main/pytorch_model.bin
439 MB
- Xet hash:
- a0d20d5d7e54c885ac9e15bba02236e0c091810de5ecbf71075fa67e7ae956fa
- Size of remote file:
- 439 MB
- SHA256:
- 394c15a1c3f38c7d03025a3ea8fa11e9b7ef013dc5772c0912338d7effbabb50
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