Instructions to use ChouBERT/ChouBERT-32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ChouBERT/ChouBERT-32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ChouBERT/ChouBERT-32")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ChouBERT/ChouBERT-32") model = AutoModelForMaskedLM.from_pretrained("ChouBERT/ChouBERT-32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2808496c83084b20d5498a3b142e725a064c4c2c40eb8617aae466eddbcd6bab
- Size of remote file:
- 445 MB
- SHA256:
- eaca186815020ee0ecae0c869a7df9c89acd37d74d333a359025dbe6a5cb243b
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