Instructions to use EricPeter/ktrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EricPeter/ktrain with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="EricPeter/ktrain")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("EricPeter/ktrain") model = AutoModelForSequenceClassification.from_pretrained("EricPeter/ktrain", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from EricPeter/ktrain: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/EricPeter/ktrain/resolve/e567ed38542aec8d4ae2dc3bd448231d73f97dc9/tokenizer.json
- Command line
-
hf download hf://EricPeter/ktrain@e567ed38542aec8d4ae2dc3bd448231d73f97dc9/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/EricPeter/ktrain/resolve/e567ed38542aec8d4ae2dc3bd448231d73f97dc9/tokenizer.json
17.1 MB
- Xet hash:
- 1fe5ed440d84f1d654390a5ce02783c8e5fc0031e54c2db4be9ef9230c7d9947
- Size of remote file:
- 17.1 MB
- SHA256:
- 5a884cbf8deb5c8eb25075bb0df14213d418c9e355319b32af46f3b8d8cdad72
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