Text Classification
Transformers
TensorBoard
Safetensors
camembert
Generated from Trainer
text-embeddings-inference
Instructions to use djamina/relatives_labels with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use djamina/relatives_labels with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="djamina/relatives_labels")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("djamina/relatives_labels") model = AutoModelForSequenceClassification.from_pretrained("djamina/relatives_labels", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from djamina/relatives_labels: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/djamina/relatives_labels/resolve/main/training_args.bin
- Command line
-
hf download hf://djamina/relatives_labels/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/djamina/relatives_labels/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 3e0a273a109482ae25dd6605946fe8f3f2dd2653d4e27cfa4f244245a2a33fa8
- Size of remote file:
- 5.11 kB
- SHA256:
- 8b9aced2eec6ae7b2fdb4989cda8a560b85c2da5e7726568188deb05275cd44f
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