Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use jkhan447/sentiment-model-sample with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jkhan447/sentiment-model-sample with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jkhan447/sentiment-model-sample")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jkhan447/sentiment-model-sample") model = AutoModelForSequenceClassification.from_pretrained("jkhan447/sentiment-model-sample", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jkhan447/sentiment-model-sample: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/jkhan447/sentiment-model-sample/resolve/main/training_args.bin
- Command line
-
hf download hf://jkhan447/sentiment-model-sample/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jkhan447/sentiment-model-sample/resolve/main/training_args.bin
3.06 kB
- Xet hash:
- ac3a98d3889a5a47b9dbfcdf3291427bdadf5feec549903f84433ac1c782f0d7
- Size of remote file:
- 3.06 kB
- SHA256:
- 8035a16f775aed25362003dd50df73847333e402977b2a0be7fcf66d479e70ef
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