Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use gsl22/finetuning-sentiment-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gsl22/finetuning-sentiment-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gsl22/finetuning-sentiment-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gsl22/finetuning-sentiment-model") model = AutoModelForSequenceClassification.from_pretrained("gsl22/finetuning-sentiment-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from gsl22/finetuning-sentiment-model: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/gsl22/finetuning-sentiment-model/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://gsl22/finetuning-sentiment-model@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/gsl22/finetuning-sentiment-model/resolve/refs%2Fpr%2F1/training_args.bin
3.96 kB
- Xet hash:
- 482b8dccbee05759e83f3a0dd48afc9aa1d111063e70eaa7beef60a00fff298a
- Size of remote file:
- 3.96 kB
- SHA256:
- aeaa300e931d745ba553584db7bfad6a106ef037ba526db784c69a7325268efd
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