Instructions to use maveriq/mybert-mini-500k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maveriq/mybert-mini-500k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="maveriq/mybert-mini-500k")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("maveriq/mybert-mini-500k") model = AutoModelForMaskedLM.from_pretrained("maveriq/mybert-mini-500k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from maveriq/mybert-mini-500k: direct link, hf CLI and curl.
- Browser
- Download file 44.8 MB
-
https://huggingface.co/maveriq/mybert-mini-500k/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://maveriq/mybert-mini-500k/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/maveriq/mybert-mini-500k/resolve/main/pytorch_model.bin
44.8 MB
- Xet hash:
- 48931391312055ffc8065c04a2e0ae011fdf292eec9a899091a19a7f66de053f
- Size of remote file:
- 44.8 MB
- SHA256:
- df2e0d40f238756bb4c04868d8491b1a871fcc2ce647748a40a16e3ffe28827b
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