Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use ASCCCCCCCC/PENGMENGJIE-finetuned-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ASCCCCCCCC/PENGMENGJIE-finetuned-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ASCCCCCCCC/PENGMENGJIE-finetuned-emotion")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ASCCCCCCCC/PENGMENGJIE-finetuned-emotion") model = AutoModelForSequenceClassification.from_pretrained("ASCCCCCCCC/PENGMENGJIE-finetuned-emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ASCCCCCCCC/PENGMENGJIE-finetuned-emotion: direct link, hf CLI and curl.
- Browser
- Download file 2.67 kB
-
https://huggingface.co/ASCCCCCCCC/PENGMENGJIE-finetuned-emotion/resolve/main/training_args.bin
- Command line
-
hf download hf://ASCCCCCCCC/PENGMENGJIE-finetuned-emotion/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ASCCCCCCCC/PENGMENGJIE-finetuned-emotion/resolve/main/training_args.bin
2.67 kB
- Xet hash:
- 0b60b350bbf903356820c724c547c777221a6dde117c402a02f5b24036b7b9ea
- Size of remote file:
- 2.67 kB
- SHA256:
- e49db71874fda22cd7bd705587c5227756dc7698c698cabc86b213356a821acb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.