Text Classification
Transformers
PyTorch
English
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use futuredatascience/welcome_video_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use futuredatascience/welcome_video_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="futuredatascience/welcome_video_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("futuredatascience/welcome_video_model") model = AutoModelForSequenceClassification.from_pretrained("futuredatascience/welcome_video_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f99e1c66f9cd7a3f14dcabcd3b37a4da7470a5a7cb0da291422156ed3decf24
- Size of remote file:
- 669 kB
- SHA256:
- bea3479edc0ed107960cd26c4921fc5a4456ee8fa9e52b2a88cc8c71231d66e5
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