Instructions to use bunoheb/emotion_classifier_main with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bunoheb/emotion_classifier_main with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bunoheb/emotion_classifier_main")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bunoheb/emotion_classifier_main") model = AutoModelForSequenceClassification.from_pretrained("bunoheb/emotion_classifier_main", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from bunoheb/emotion_classifier_main: direct link, hf CLI and curl.
- Browser
- Download file 1.35 GB
-
https://huggingface.co/bunoheb/emotion_classifier_main/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://bunoheb/emotion_classifier_main/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/bunoheb/emotion_classifier_main/resolve/main/pytorch_model.bin
1.35 GB
- Xet hash:
- e97065af3a7746779a603dceefdc0b164432bf6c3b2a0bfee9db4b12c5388cf6
- Size of remote file:
- 1.35 GB
- SHA256:
- b65dc9277d7055508f9249cc74b63e619d3b5691f3900fb3ff45d8708fcbd66a
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