Text Classification
Transformers
PyTorch
TensorBoard
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use devtanumisra/finetuning-hatespeech-model-deberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devtanumisra/finetuning-hatespeech-model-deberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="devtanumisra/finetuning-hatespeech-model-deberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("devtanumisra/finetuning-hatespeech-model-deberta") model = AutoModelForSequenceClassification.from_pretrained("devtanumisra/finetuning-hatespeech-model-deberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
#1
by librarian-bot - opened
README.md
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@@ -6,6 +6,7 @@ metrics:
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- accuracy
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- precision
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- recall
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model-index:
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- name: finetuning-hatespeech-model-deberta
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results: []
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- accuracy
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- precision
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- recall
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base_model: yangheng/deberta-v3-base-absa-v1.1
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model-index:
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- name: finetuning-hatespeech-model-deberta
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results: []
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