Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use joebobby/finetuning-sentiment-model-5000-samples3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joebobby/finetuning-sentiment-model-5000-samples3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="joebobby/finetuning-sentiment-model-5000-samples3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("joebobby/finetuning-sentiment-model-5000-samples3") model = AutoModelForSequenceClassification.from_pretrained("joebobby/finetuning-sentiment-model-5000-samples3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from joebobby/finetuning-sentiment-model-5000-samples3: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/joebobby/finetuning-sentiment-model-5000-samples3/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://joebobby/finetuning-sentiment-model-5000-samples3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/joebobby/finetuning-sentiment-model-5000-samples3/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 6506ba9579a39e943527420e4f6262e83bbb5a64d7f291d8fb1b15cf9a781817
- Size of remote file:
- 438 MB
- SHA256:
- a271e1410ad8d1dcbbf4a025ed19b512d25575f70995d09f5ca1538718cd3a6e
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