Feature Extraction
Transformers
Safetensors
ntv3_tracks
genomics
dna
biology
ntv3
long-range
functional-genomics
custom_code
Instructions to use InstaDeepAI/NTv3_tracks with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InstaDeepAI/NTv3_tracks with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="InstaDeepAI/NTv3_tracks", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("InstaDeepAI/NTv3_tracks", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Explain the region interface and tighten the card
#4
by ybornachot - opened
Answers #3. The region-interface paragraph only made sense if you already knew the pipeline downloads the window from UCSC; it now says so, says which assembly UCSC can't serve (wheat), and what out.coordinates covers.
Also a style pass: drops filler and repeated sentences (intro claim, the track-order aside, the soft-masking and crop paragraphs, out-of-scope wording), and replaces "Citation to be added on publication" with the preprint BibTeX used on the ntv3 Space.
π€ Generated with Claude Code
ybornachot changed pull request status to merged