Instructions to use alphaedge-ai/mmBERT-base-ben-32768 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alphaedge-ai/mmBERT-base-ben-32768 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="alphaedge-ai/mmBERT-base-ben-32768")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("alphaedge-ai/mmBERT-base-ben-32768") model = AutoModel.from_pretrained("alphaedge-ai/mmBERT-base-ben-32768", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c26b6a3482b1787bd59ec97fa73f9ed0e93f96ab7b07996313516d84f41d726c
- Size of remote file:
- 542 MB
- SHA256:
- a0e3367599dc9aa50a0b9f52f791fb515ce008c558f05087971b623063928d4d
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