Instructions to use julien-c/dummy-diff-tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use julien-c/dummy-diff-tokenizer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="julien-c/dummy-diff-tokenizer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("julien-c/dummy-diff-tokenizer") model = AutoModelForMaskedLM.from_pretrained("julien-c/dummy-diff-tokenizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from julien-c/dummy-diff-tokenizer: direct link, hf CLI and curl.
- Browser
- Download file 157 kB
-
https://huggingface.co/julien-c/dummy-diff-tokenizer/resolve/main/tf_model.h5
- Command line
-
hf download hf://julien-c/dummy-diff-tokenizer/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/julien-c/dummy-diff-tokenizer/resolve/main/tf_model.h5
157 kB
- Xet hash:
- 270a8b1acf605b95419149ae1c5a7a11ba13dc005d0ae582da2cdf4752251455
- Size of remote file:
- 157 kB
- SHA256:
- 4a8fce317e36e320941d2d200a1747c94d2a8ee0b24c8289522b579ea53eac40
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