Instructions to use hf-tiny-model-private/tiny-random-Data2VecTextForMaskedLM 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-Data2VecTextForMaskedLM 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-Data2VecTextForMaskedLM")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-Data2VecTextForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-tiny-model-private/tiny-random-Data2VecTextForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-Data2VecTextForMaskedLM: direct link, hf CLI and curl.
- Browser
- Download file 358 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-Data2VecTextForMaskedLM/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-Data2VecTextForMaskedLM@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-Data2VecTextForMaskedLM/resolve/refs%2Fpr%2F1/model.safetensors
358 kB
- Xet hash:
- c8111556d448d4fbf765d92b4277f2ed67e6ecb06cb795e7b6a49fe5de1df0a5
- Size of remote file:
- 358 kB
- SHA256:
- 695959e616b8582b3244af3c5d8ff855af3211de621896c311fb6528c1e8debd
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