Text Classification
Transformers
TensorBoard
Safetensors
bert
10_class
multi_labels
Generated from Trainer
text-embeddings-inference
Instructions to use eedeedeed/1008model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eedeedeed/1008model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="eedeedeed/1008model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("eedeedeed/1008model") model = AutoModelForSequenceClassification.from_pretrained("eedeedeed/1008model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 14e290e7d99786afcd9340e3e028e06f93d9ccd79a8b63d065c51f9afa970e4b
- Size of remote file:
- 5.18 kB
- SHA256:
- 3ee671c2cb4825251462df1b4594f61d18bd7db7cda1ed9c0799e00fc98e567c
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