Instructions to use ssun32/bert_twitter_turkle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ssun32/bert_twitter_turkle with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ssun32/bert_twitter_turkle")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ssun32/bert_twitter_turkle") model = AutoModel.from_pretrained("ssun32/bert_twitter_turkle", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 696c67fdcf773787601d0c60b96e15575489d121456652a81d83a345d58238b6
- Size of remote file:
- 433 MB
- SHA256:
- 5a57af77445bb592a4b1b2168051bae45ad18167aa1125d1fd15348bd4b7a70d
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