Text Classification
Transformers
TensorBoard
Safetensors
bert
HHD
10_class
multi_labels
Generated from Trainer
text-embeddings-inference
Instructions to use sourblue/model_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sourblue/model_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sourblue/model_output")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sourblue/model_output") model = AutoModelForSequenceClassification.from_pretrained("sourblue/model_output") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fbbe7427b8c9371c64577cef4693bd81945d9451960271021aece4a01ab6c542
- Size of remote file:
- 5.18 kB
- SHA256:
- 6a946ab7016d89cd3c5dc2e5405d30396de1bcf182dd9fffb72344c4a7542df6
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