Instructions to use m0pper/chunky_babyberta_lsc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m0pper/chunky_babyberta_lsc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="m0pper/chunky_babyberta_lsc")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("m0pper/chunky_babyberta_lsc") model = AutoModelForMaskedLM.from_pretrained("m0pper/chunky_babyberta_lsc") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a59f89c2a795889cb1231ad29c980af1e98296e0c3699d1f0701410bd0e2384
- Size of remote file:
- 167 MB
- SHA256:
- 51f43fdba0a188977087b179fa93eb136d7665ae15cefb7fa92b1b01220d8ee8
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