Text Classification
Transformers
Safetensors
English
numo
feature-extraction
gemma4
custom-code
scientific-literature
study-design
decision-model
calibrated
local-inference
custom_code
Instructions to use mycel-ai/Numo-1-E2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mycel-ai/Numo-1-E2B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mycel-ai/Numo-1-E2B", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mycel-ai/Numo-1-E2B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Ctrl+K
- assets
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