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 pytorch_model.bin from jkhan447/sentiment-model-sample: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/jkhan447/sentiment-model-sample/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jkhan447/sentiment-model-sample/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jkhan447/sentiment-model-sample/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 9888d8e1bb37c3025625f24c68400f1d3ed44b2b17d05d9581fceeff19d221b5
- Size of remote file:
- 438 MB
- SHA256:
- 657c78793ec82397cb6703b5e39509b9927c7ffe098e6eb372a6990d528aa23b
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