Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use marcelcastrobr/sagemaker-distilbert-emotion-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcelcastrobr/sagemaker-distilbert-emotion-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marcelcastrobr/sagemaker-distilbert-emotion-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marcelcastrobr/sagemaker-distilbert-emotion-2") model = AutoModelForSequenceClassification.from_pretrained("marcelcastrobr/sagemaker-distilbert-emotion-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from marcelcastrobr/sagemaker-distilbert-emotion-2: direct link, hf CLI and curl.
- Browser
- Download file 2.99 kB
-
https://huggingface.co/marcelcastrobr/sagemaker-distilbert-emotion-2/resolve/main/training_args.bin
- Command line
-
hf download hf://marcelcastrobr/sagemaker-distilbert-emotion-2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/marcelcastrobr/sagemaker-distilbert-emotion-2/resolve/main/training_args.bin
2.99 kB
- Xet hash:
- 9aa068b6bde2f18949c153003b2324022fcbb4e03b54dea369b034fc4f4eaf06
- Size of remote file:
- 2.99 kB
- SHA256:
- 590ea92be874becebbc4326548b36910da9c64156bec9847fc9bbc1a53464f21
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