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")# 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 pytorch_model.bin from gsl22/finetuning-sentiment-model: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/gsl22/finetuning-sentiment-model/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://gsl22/finetuning-sentiment-model@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gsl22/finetuning-sentiment-model/resolve/refs%2Fpr%2F1/pytorch_model.bin
268 MB
- Xet hash:
- d6e6c96b846df791bd63b4cf35292da5365d75ecb2b2c534896ff6a3bc24f569
- Size of remote file:
- 268 MB
- SHA256:
- 635b24f97bd99efb2ac56d783fae12422f7e848241171fb46a2a7c596926d37b
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