Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Junr-syl/sentiments_analysis_upgrade with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Junr-syl/sentiments_analysis_upgrade with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Junr-syl/sentiments_analysis_upgrade")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Junr-syl/sentiments_analysis_upgrade") model = AutoModelForSequenceClassification.from_pretrained("Junr-syl/sentiments_analysis_upgrade", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Junr-syl/sentiments_analysis_upgrade: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/Junr-syl/sentiments_analysis_upgrade/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Junr-syl/sentiments_analysis_upgrade/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Junr-syl/sentiments_analysis_upgrade/resolve/main/pytorch_model.bin
433 MB
- Xet hash:
- 7d0bb9dab0629d0f4039eaa36b06480bbc62cb0a34ba7857d4c1d59931425984
- Size of remote file:
- 433 MB
- SHA256:
- d5ecc193e95640443e130a686c77b1b0588ac839677bb7deb7e40f7fe1f23fb8
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