Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Carick/distilbert-base-uncased-wordnet_dataset_three-fine-tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Carick/distilbert-base-uncased-wordnet_dataset_three-fine-tuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Carick/distilbert-base-uncased-wordnet_dataset_three-fine-tuned")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Carick/distilbert-base-uncased-wordnet_dataset_three-fine-tuned") model = AutoModelForSequenceClassification.from_pretrained("Carick/distilbert-base-uncased-wordnet_dataset_three-fine-tuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Carick/distilbert-base-uncased-wordnet_dataset_three-fine-tuned: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/Carick/distilbert-base-uncased-wordnet_dataset_three-fine-tuned/resolve/main/training_args.bin
- Command line
-
hf download hf://Carick/distilbert-base-uncased-wordnet_dataset_three-fine-tuned/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/Carick/distilbert-base-uncased-wordnet_dataset_three-fine-tuned/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- d1e4a2b4a903049ed4dc32183e44d267fdcf1f313fc4ff40f1276ad2168dec55
- Size of remote file:
- 5.43 kB
- SHA256:
- 2162f8503e6c624885534c20a592497de39381d3c0205c5e53e2b8516853bdbe
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