Instructions to use dicta-il/dictabert-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dicta-il/dictabert-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dicta-il/dictabert-tiny")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dicta-il/dictabert-tiny") model = AutoModelForMaskedLM.from_pretrained("dicta-il/dictabert-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dicta-il/dictabert-tiny: direct link, hf CLI and curl.
- Browser
- Download file 180 MB
-
https://huggingface.co/dicta-il/dictabert-tiny/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dicta-il/dictabert-tiny/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dicta-il/dictabert-tiny/resolve/main/pytorch_model.bin
180 MB
- Xet hash:
- 5f087b635008067b945ded14fc60d670b5f8e95d6aa978d2778e74b59125fb65
- Size of remote file:
- 180 MB
- SHA256:
- 542dd6ca6a173b73d4d5827722e138b9746635480ae852c613219609a30d8956
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