Instructions to use fjluque/dummy-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fjluque/dummy-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="fjluque/dummy-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("fjluque/dummy-model") model = AutoModelForMaskedLM.from_pretrained("fjluque/dummy-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from fjluque/dummy-model: direct link, hf CLI and curl.
- Browser
- Download file 543 MB
-
https://huggingface.co/fjluque/dummy-model/resolve/main/tf_model.h5
- Command line
-
hf download hf://fjluque/dummy-model/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/fjluque/dummy-model/resolve/main/tf_model.h5
543 MB
- Xet hash:
- ffdf8cfe0b4f70a8c24f18ebbd4bd6ee577159c56c40f0c660889e904fe3b787
- Size of remote file:
- 543 MB
- SHA256:
- ac29e2b2a661b7631df0e7b705766a418601335ef1fb380768d1a0bf17c422ab
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