Text Classification
Transformers
Safetensors
modernbert
multi_label_classification
Generated from Trainer
text-embeddings-inference
Instructions to use joheras/finetuned_model_emotion_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joheras/finetuned_model_emotion_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="joheras/finetuned_model_emotion_detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("joheras/finetuned_model_emotion_detection") model = AutoModelForSequenceClassification.from_pretrained("joheras/finetuned_model_emotion_detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from joheras/finetuned_model_emotion_detection: direct link, hf CLI and curl.
- Browser
- Download file 5.84 kB
-
https://huggingface.co/joheras/finetuned_model_emotion_detection/resolve/main/training_args.bin
- Command line
-
hf download hf://joheras/finetuned_model_emotion_detection/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/joheras/finetuned_model_emotion_detection/resolve/main/training_args.bin
5.84 kB
- Xet hash:
- 94702bc225c1eae61abf0e17f7f08e7df7e7172eafab0cbb8ef8dee3fed1176b
- Size of remote file:
- 5.84 kB
- SHA256:
- b979729f79aef0f3d88793d40711e4c4bc7d754393ee6a321d3e695634150d68
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