Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use jelinek/finetuning-sentiment-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jelinek/finetuning-sentiment-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jelinek/finetuning-sentiment-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jelinek/finetuning-sentiment-model") model = AutoModelForSequenceClassification.from_pretrained("jelinek/finetuning-sentiment-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jelinek/finetuning-sentiment-model: direct link, hf CLI and curl.
- Browser
- Download file 3.95 kB
-
https://huggingface.co/jelinek/finetuning-sentiment-model/resolve/main/training_args.bin
- Command line
-
hf download hf://jelinek/finetuning-sentiment-model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jelinek/finetuning-sentiment-model/resolve/main/training_args.bin
3.95 kB
- Xet hash:
- f55657c1c8a1c668b21a791d26f819ab28b0c06caad3667cd682ce5d6c66e825
- Size of remote file:
- 3.95 kB
- SHA256:
- 2dc1e232794f309ddefcf270365f28be1e244bcd4c129f22fb42b92b072a91bf
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