Text Classification
Transformers
TensorBoard
Safetensors
bert
LMH
10_class
multi_labels
Generated from Trainer
text-embeddings-inference
Instructions to use czarmagnate/1008model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use czarmagnate/1008model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="czarmagnate/1008model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("czarmagnate/1008model") model = AutoModelForSequenceClassification.from_pretrained("czarmagnate/1008model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5500ce32916ca0de317ca978e2f40be26b989944ba6f4bfa73b49704076b2eb2
- Size of remote file:
- 5.18 kB
- SHA256:
- e9bc05ab91640bf434e65415a7a80d7154386d87506c882873ebeeeb3c23a9a2
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