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 pytorch_model.bin from jelinek/finetuning-sentiment-model: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/jelinek/finetuning-sentiment-model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jelinek/finetuning-sentiment-model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jelinek/finetuning-sentiment-model/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 8654bb7f1f10fabddd3777e2ef335b1a443f1c3034bc16a758e8b05ae4508bec
- Size of remote file:
- 268 MB
- SHA256:
- 0a28ac8e895655cf5556eddfc1fa3df8a5571ad4ecde00448d25951a496a9e78
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