Instructions to use interneuronai/classifying_member_activity_levels_distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use interneuronai/classifying_member_activity_levels_distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="interneuronai/classifying_member_activity_levels_distilbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("interneuronai/classifying_member_activity_levels_distilbert") model = AutoModelForSequenceClassification.from_pretrained("interneuronai/classifying_member_activity_levels_distilbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d14dbc20ba74a93e04737621fec64bdc2e0962152101c175a1d6d5189c76c704
- Size of remote file:
- 541 MB
- SHA256:
- 9d79571f2f28592a355c6a8e57aea0e7118830761c441541687505e5de4ee352
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