Instructions to use digio/BERTweet-base_1000000s_all_MNRL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use digio/BERTweet-base_1000000s_all_MNRL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="digio/BERTweet-base_1000000s_all_MNRL")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("digio/BERTweet-base_1000000s_all_MNRL") model = AutoModel.from_pretrained("digio/BERTweet-base_1000000s_all_MNRL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0b3a2431ee7262ec287c2b6668c47b273dd8651f37d1c0d1093b7d9a0c2e8558
- Size of remote file:
- 540 MB
- SHA256:
- 2171deacea4885f1d859e0d011f5c1c6831226c956f3a65346be13d9cb964cc1
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