Instructions to use fjluque/dummy-model2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fjluque/dummy-model2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="fjluque/dummy-model2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("fjluque/dummy-model2") model = AutoModelForMaskedLM.from_pretrained("fjluque/dummy-model2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from fjluque/dummy-model2: direct link, hf CLI and curl.
- Browser
- Download file 543 MB
-
https://huggingface.co/fjluque/dummy-model2/resolve/main/tf_model.h5
- Command line
-
hf download hf://fjluque/dummy-model2/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/fjluque/dummy-model2/resolve/main/tf_model.h5
543 MB
- Xet hash:
- d55395873c476721501132fec4c5d5c716d13ceaa0f9419482da0303fa505a95
- Size of remote file:
- 543 MB
- SHA256:
- 42d4e4bd859e929aaedebeda7c745fc6d8a0d42a55325b8c5eec207144b5c044
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