Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use Yashodhar29/deberta-v3-base-cpp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yashodhar29/deberta-v3-base-cpp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Yashodhar29/deberta-v3-base-cpp")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Yashodhar29/deberta-v3-base-cpp") model = AutoModelForSequenceClassification.from_pretrained("Yashodhar29/deberta-v3-base-cpp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Yashodhar29/deberta-v3-base-cpp: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/Yashodhar29/deberta-v3-base-cpp/resolve/main/training_args.bin
- Command line
-
hf download hf://Yashodhar29/deberta-v3-base-cpp/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Yashodhar29/deberta-v3-base-cpp/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- 9347a598c892e7f34bf95d9c6b4ee9f5bfa5958cc538df0d752a48ef89393d51
- Size of remote file:
- 5.43 kB
- SHA256:
- 4ba9a51e7a35a2780181a3d9a5e1dde90ca55599da4db783154fc352526b3546
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