Instructions to use cabrooks/LOGION-50k_wordpiece with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cabrooks/LOGION-50k_wordpiece with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="cabrooks/LOGION-50k_wordpiece")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("cabrooks/LOGION-50k_wordpiece") model = AutoModelForMaskedLM.from_pretrained("cabrooks/LOGION-50k_wordpiece", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from cabrooks/LOGION-50k_wordpiece: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/cabrooks/LOGION-50k_wordpiece/resolve/main/training_args.bin
- Command line
-
hf download hf://cabrooks/LOGION-50k_wordpiece/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/cabrooks/LOGION-50k_wordpiece/resolve/main/training_args.bin
3.06 kB
- Xet hash:
- 781b78ed689bd43a84d586faaafbc1d630744bae559fa039c8b140c68864ae4c
- Size of remote file:
- 3.06 kB
- SHA256:
- 4711a71b9186331cd1e18fac6f3b227f10b844f6ca8c1166fc919684598d857a
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