Instructions to use hf-tiny-model-private/tiny-random-MPNetForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-MPNetForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-tiny-model-private/tiny-random-MPNetForMaskedLM")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-MPNetForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-tiny-model-private/tiny-random-MPNetForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-MPNetForMaskedLM: direct link, hf CLI and curl.
- Browser
- Download file 960 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-MPNetForMaskedLM/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-MPNetForMaskedLM@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-MPNetForMaskedLM/resolve/refs%2Fpr%2F1/model.safetensors
960 kB
- Xet hash:
- b94d331f00bb0edbb41d22ab5c4740319d812420df87b30656d41128f7436693
- Size of remote file:
- 960 kB
- SHA256:
- e941395c6ed45a48fdb47b424aa6765aa03b9d2b0be3666b4089e79f4093699b
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