Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use msgfrom96/emotion_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use msgfrom96/emotion_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="msgfrom96/emotion_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("msgfrom96/emotion_model") model = AutoModelForSequenceClassification.from_pretrained("msgfrom96/emotion_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8984db96a19c84c99d2fcc8469452b50e531296bb53fa20210ac5a7e9fe7d33f
- Size of remote file:
- 2.24 GB
- SHA256:
- 5802f6c4a5ff334b7ad51926ad3182d01cd1d98507ff35ce1a9fa0c1d9d82e54
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