Feature Extraction
Transformers
Safetensors
malecns
connectome
fruit-fly
drosophila
neuroscience
graph
custom_code
Instructions to use QuixiAI/MaleCNS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use QuixiAI/MaleCNS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="QuixiAI/MaleCNS", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("QuixiAI/MaleCNS", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model card: stand-alone; no FlyGPT references beyond build-script provenance
Browse files
README.md
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@@ -17,8 +17,7 @@ presynaptic neuron's predicted neurotransmitter, rescales the whole matrix to a
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projections, per-neuron gains, and a readout around it. Those are good modeling decisions for that project, but
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they are baked into its weights, so anyone who wants the connectome for something else has to undo them or go back
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to the raw release. This repository is the layer underneath: the **source connectome, unmodified**, so that
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fly-llm-hf,
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lossless tensors. At a high level the differences are:
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- **Whole nervous system, not a subset.** Every body in the release's connectivity file: brain, optic lobes, and
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ventral nerve cord, with subsets available as masks rather than chosen for you.
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| `transformers` role | `AutoModel` returning the graph | `AutoModelForCausalLM` generating text |
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```text
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Janelia MaleCNS v1.0 ──► this repository (synapse counts, untouched) ──►
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Janelia MaleCNS v1.0 ──► Xenova packaging ──► fly-llm-hf (signed, rescaled, frozen reservoir + TinyStories readout)
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```
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## Provenance
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Built by [`data/fly/export_malecns_hf.py`](https://github.com/QuixiAI/FlyGPT) from these files in
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`gs://flyem-male-cns/v1.0/connectome-data/flat-connectome/`, md5-verified against the bucket listing:
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| role | file | md5 (base64) |
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Official site: https://male-cns.janelia.org · neuPrint dataset `male-cns:v1.0`.
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This repository is the data backbone of [FlyGPT](https://github.com/QuixiAI/FlyGPT), which trains a language model
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whose recurrent architecture is a subgraph of this connectome, with its own trainable edge weights.
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projections, per-neuron gains, and a readout around it. Those are good modeling decisions for that project, but
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they are baked into its weights, so anyone who wants the connectome for something else has to undo them or go back
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to the raw release. This repository is the layer underneath: the **source connectome, unmodified**, so that
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fly-llm-hf, downstream models, graph-ML work, and simulations can all start from the same lossless tensors. At a high level the differences are:
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- **Whole nervous system, not a subset.** Every body in the release's connectivity file: brain, optic lobes, and
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ventral nerve cord, with subsets available as masks rather than chosen for you.
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| `transformers` role | `AutoModel` returning the graph | `AutoModelForCausalLM` generating text |
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```text
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Janelia MaleCNS v1.0 ──► this repository (synapse counts, untouched) ──► your model (whatever weights you derive from them)
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Janelia MaleCNS v1.0 ──► Xenova packaging ──► fly-llm-hf (signed, rescaled, frozen reservoir + TinyStories readout)
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```
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## Provenance
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Built by the script [`data/fly/export_malecns_hf.py`](https://github.com/QuixiAI/FlyGPT/blob/main/data/fly/export_malecns_hf.py) from these files in
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`gs://flyem-male-cns/v1.0/connectome-data/flat-connectome/`, md5-verified against the bucket listing:
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| role | file | md5 (base64) |
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Official site: https://male-cns.janelia.org · neuPrint dataset `male-cns:v1.0`.
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