Instructions to use dd3434/test_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dd3434/test_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dd3434/test_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dd3434/test_model") model = AutoModelForSequenceClassification.from_pretrained("dd3434/test_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spiece.model from dd3434/test_model: direct link, hf CLI and curl.
- Browser
- Download file 371 kB
-
https://huggingface.co/dd3434/test_model/resolve/main/spiece.model
- Command line
-
hf download hf://dd3434/test_model/spiece.model
-
curl -L -o spiece.model https://huggingface.co/dd3434/test_model/resolve/main/spiece.model
371 kB
- Xet hash:
- 524a2b746b381c74d61ef764ae9cb61e186b3af53ba134c5c81a9f9771f581d1
- Size of remote file:
- 371 kB
- SHA256:
- 17dc471055592d3cc9e0a5831e769246a8a001a4d27551c9ed79668173c7b407
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