Text Classification
Transformers
Safetensors
English
bert
sentiment-analysis
multi-label
mental-health
text-embeddings-inference
Instructions to use Sharath45/MENTALBERT_MULTILABEL_CLASSIFICATION with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sharath45/MENTALBERT_MULTILABEL_CLASSIFICATION with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sharath45/MENTALBERT_MULTILABEL_CLASSIFICATION")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sharath45/MENTALBERT_MULTILABEL_CLASSIFICATION") model = AutoModelForSequenceClassification.from_pretrained("Sharath45/MENTALBERT_MULTILABEL_CLASSIFICATION") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bb18f2b9fdd77efa284b6abe90530a8321c93e168176f7b5cf1fe718272edc57
- Size of remote file:
- 5.3 kB
- SHA256:
- b709926443f6c2ece83caf7740fe493ac76710e5a029faf6f070c74bdbb1bd76
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