Instructions to use alphaedge-ai/mmBERT-base-32k-yarn-zho-16384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alphaedge-ai/mmBERT-base-32k-yarn-zho-16384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="alphaedge-ai/mmBERT-base-32k-yarn-zho-16384")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("alphaedge-ai/mmBERT-base-32k-yarn-zho-16384") model = AutoModelForMaskedLM.from_pretrained("alphaedge-ai/mmBERT-base-32k-yarn-zho-16384", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7f0860d88a4328f321bd5d8d0b063ef5d34aea69ad2c1ca0d03dd67a34e5db3f
- Size of remote file:
- 271 MB
- SHA256:
- 79b2e623c3a5164812d5a95212779df6ee707042dd077927ff9d84c04279d26a
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