Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Junr-syl/sentiments_analysis_DISTILBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Junr-syl/sentiments_analysis_DISTILBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Junr-syl/sentiments_analysis_DISTILBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Junr-syl/sentiments_analysis_DISTILBERT") model = AutoModelForSequenceClassification.from_pretrained("Junr-syl/sentiments_analysis_DISTILBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Junr-syl/sentiments_analysis_DISTILBERT: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/Junr-syl/sentiments_analysis_DISTILBERT/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Junr-syl/sentiments_analysis_DISTILBERT/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Junr-syl/sentiments_analysis_DISTILBERT/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 8d56c944b395e797378625443e1f15b57ff0f24e1a0bd6e694f0a8bad5a9f057
- Size of remote file:
- 268 MB
- SHA256:
- e129b328975c7bff16c558aebeac3056979767c89c96003debc052b33d4dc922
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