Text Classification
Transformers
Safetensors
English
bert
multi-label
theme_detection
mentorship
entrepreneurship
startup success
json automation
text-embeddings-inference
Instructions to use 4nkh/theme_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 4nkh/theme_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="4nkh/theme_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("4nkh/theme_model") model = AutoModelForSequenceClassification.from_pretrained("4nkh/theme_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78bcb8aae54572bdd44733841b715fe4866373397af89654438f81b8dcddad30
- Size of remote file:
- 5.84 kB
- SHA256:
- 8efdc88e25541d9081abb2581b27ce3604a78933021e01c95e055253fdaa9c60
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