Feature Extraction
Transformers
Safetensors
ntv3_tracks
genomics
dna
biology
ntv3
long-range
functional-genomics
custom_code
Instructions to use InstaDeepAI/NTv3_tracks_1mb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InstaDeepAI/NTv3_tracks_1mb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="InstaDeepAI/NTv3_tracks_1mb", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("InstaDeepAI/NTv3_tracks_1mb", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
docs: reuse the model's out in the channel-order snippet
#3
by Yanisadel - opened
The snippet under Reading the predictions reads outputs["bigwig_tracks_logits"], but no outputs is defined on the card: it raises NameError: name 'outputs' is not defined. It means the model output from Usage, out, so this renames it. Nothing else changes.
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Yanisadel changed pull request title from docs: define outputs in the channel-order snippet to docs: reuse the model's out in the channel-order snippet
Yanisadel changed pull request status to merged