Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use jpabbuehl/sagemaker-distilbert-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jpabbuehl/sagemaker-distilbert-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jpabbuehl/sagemaker-distilbert-emotion")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jpabbuehl/sagemaker-distilbert-emotion") model = AutoModelForSequenceClassification.from_pretrained("jpabbuehl/sagemaker-distilbert-emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jpabbuehl/sagemaker-distilbert-emotion: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/jpabbuehl/sagemaker-distilbert-emotion/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jpabbuehl/sagemaker-distilbert-emotion/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jpabbuehl/sagemaker-distilbert-emotion/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 89746653ba80c0ae19570a24964e4126c1c6b1ec87c36741a2568eb05888648d
- Size of remote file:
- 268 MB
- SHA256:
- c670c7f1b257cc647e2e2e2b08c89b4903652e41ea3c2a2a2060ffd552667700
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