Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use kiatkock/sentiment_pc_under_sampler with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kiatkock/sentiment_pc_under_sampler with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kiatkock/sentiment_pc_under_sampler")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kiatkock/sentiment_pc_under_sampler") model = AutoModelForSequenceClassification.from_pretrained("kiatkock/sentiment_pc_under_sampler", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from kiatkock/sentiment_pc_under_sampler: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/kiatkock/sentiment_pc_under_sampler/resolve/main/training_args.bin
- Command line
-
hf download hf://kiatkock/sentiment_pc_under_sampler/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/kiatkock/sentiment_pc_under_sampler/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 82e633e53c9b94b6248e6592cf49040bd3135bfa3c66b9a90b4afb1827f42b3f
- Size of remote file:
- 5.11 kB
- SHA256:
- c33ad7c0c3aee6549618b12f0e11004c3fe1cdaa7f64df3f932119e5405d5f82
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