Instructions to use TypicaAI/magbert-lm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TypicaAI/magbert-lm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="TypicaAI/magbert-lm")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("TypicaAI/magbert-lm") model = AutoModelForMaskedLM.from_pretrained("TypicaAI/magbert-lm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from TypicaAI/magbert-lm: direct link, hf CLI and curl.
- Browser
- Download file 1.78 kB
-
https://huggingface.co/TypicaAI/magbert-lm/resolve/8346c6bdbb798a69bd877e8aaf7246b5f2a501a3/training_args.bin
- Command line
-
hf download hf://TypicaAI/magbert-lm@8346c6bdbb798a69bd877e8aaf7246b5f2a501a3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/TypicaAI/magbert-lm/resolve/8346c6bdbb798a69bd877e8aaf7246b5f2a501a3/training_args.bin
1.78 kB
- Xet hash:
- a397143ad8bda0f56187eaed8294adf99595da5508ca50755cfdd170a3a2265d
- Size of remote file:
- 1.78 kB
- SHA256:
- 91193d28ca2f641953ec26fe69d499f7011c078853cdb7ef9eb0d6a77cd70dd4
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