Text Classification
Transformers
TensorBoard
Safetensors
camembert
Generated from Trainer
text-embeddings-inference
Instructions to use spidersouris/dmodels with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use spidersouris/dmodels with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="spidersouris/dmodels")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("spidersouris/dmodels") model = AutoModelForSequenceClassification.from_pretrained("spidersouris/dmodels", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7a25bd96bb9d4d510146b3d0dcb246d118ed18f5a498bcc77035fb4ecd3dbf95
- Size of remote file:
- 5.18 kB
- SHA256:
- be0988ce7fab801e2b7d1c7cb5ca3a8b988537ff51485aaabcff3d8bb8ea67d0
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