Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use tminhtri1910/codebert_paravul with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tminhtri1910/codebert_paravul with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tminhtri1910/codebert_paravul")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tminhtri1910/codebert_paravul") model = AutoModelForSequenceClassification.from_pretrained("tminhtri1910/codebert_paravul", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from tminhtri1910/codebert_paravul: direct link, hf CLI and curl.
- Browser
- Download file 5.84 kB
-
https://huggingface.co/tminhtri1910/codebert_paravul/resolve/main/training_args.bin
- Command line
-
hf download hf://tminhtri1910/codebert_paravul/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/tminhtri1910/codebert_paravul/resolve/main/training_args.bin
5.84 kB
- Xet hash:
- d6bbf2ce60cb38568e239edb902633fab1b73758d3503697dea994f73928f5e2
- Size of remote file:
- 5.84 kB
- SHA256:
- a512b431a22bec12970297ad51378f587f04917dd73d061395a5429a30f4c455
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