Datasets:

MateusGSM
/

FlySLM

ArXiv:

Tags:

connectome

drosophila

spiking-neural-network

License:

Dataset card Files Files and versions

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Dataset Viewer

The dataset viewer is not available for this subset.

Cannot get the split names for the config 'default' of the dataset.

Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/parquet/parquet.py", line 127, in _split_generators
                  self.info.features = datasets.Features.from_arrow_schema(pq.read_schema(f))
                                                                           ~~~~~~~~~~~~~~^^^
                File "/usr/local/lib/python3.14/site-packages/pyarrow/parquet/core.py", line 2459, in read_schema
                  file = ParquetFile(
                      where, memory_map=memory_map,
                      decryption_properties=decryption_properties)
                File "/usr/local/lib/python3.14/site-packages/pyarrow/parquet/core.py", line 328, in __init__
                  self.reader.open(
                  ~~~~~~~~~~~~~~~~^
                      source, use_memory_map=memory_map,
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ...<8 lines>...
                      arrow_extensions_enabled=arrow_extensions_enabled,
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "pyarrow/_parquet.pyx", line 1656, in pyarrow._parquet.ParquetReader.open
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 68, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ~~~~~~~~~~~~~~~~~~~~~~~^
                      path=dataset,
                      ^^^^^^^^^^^^^
                      config_name=config,
                      ^^^^^^^^^^^^^^^^^^^
                      token=hf_token,
                      ^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                      path,
                  ...<6 lines>...
                      **config_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

FlySLM run-time data

Everything the FlySLM app downloads after installation, mirrored in one place so that a moved or changed upstream link can never break an installation: the fly-brain wiring data (connectomes), the conversation-data sources, the local helper and translator models, the llama.cpp runtime for every platform and the pre-trained Fly AI brains.

FlySLM pins a commit of this dataset and verifies every file by size and SHA-256 before using it (manifest.json lists them). The original source of every file is recorded below; FlySLM never downloads from there.

Licences differ per file and are the original ones (this mirror changes nothing). Some conversation sources are non-commercial (DailyDialog CC-BY-NC-SA-4.0, EmpatheticDialogues CC-BY-NC-4.0); databricks-dolly-15k is CC-BY-SA-3.0 and TinyStories CDLA-Sharing-1.0 (share-alike). The connectomes are CC-BY 4.0: cite the papers below.

Layout

Folder	Contents
`helper/`	Gemma 4 12B (QAT, 4-bit GGUF) and its vision projector: the local AI Helper
`translator/`	Hy-MT2 1.8B (6-bit GGUF): the local translator
`runtime/llama.cpp-b11146/`	unmodified official llama.cpp release archives (Windows, Linux, macOS)
`connectomes/`	raw FlyWire FAFB v783 and MaleCNS v1.0 files, as published
`corpus/`	the conversation and text sources FlySLM builds its training dataset from, as published
`brains/`	pre-trained Fly AI brains (FlySLM/m and FlySLM/f) with their training records

Files

Path	Size	Licence	Original source
`helper/gemma-4-12b-it-qat-q4_0/gemma-4-12b-it-qat-q4_0.gguf`	6,652.7 MB	Apache-2.0	https://huggingface.co/google/gemma-4-12b-it-qat-q4_0-gguf @ 29d097773436b69ff9feafd636ab4cf873786537
`helper/gemma-4-12b-it-qat-q4_0/mmproj-gemma-4-12b-it-qat-q4_0.gguf`	167.0 MB	Apache-2.0	https://huggingface.co/google/gemma-4-12b-it-qat-q4_0-gguf @ 29d097773436b69ff9feafd636ab4cf873786537
`translator/hy-mt2-1.8b/Hy-MT2-1.8B-Q6_K.gguf`	1,406.5 MB	Apache-2.0	https://huggingface.co/tencent/Hy-MT2-1.8B-GGUF @ a0c709d9fac510f2c807aa3af52872340dc37a4a
`runtime/llama.cpp-b11146/llama-b11146-bin-win-vulkan-x64.zip`	30.6 MB	MIT	https://github.com/ggml-org/llama.cpp/releases/download/b11146/llama-b11146-bin-win-vulkan-x64.zip
`runtime/llama.cpp-b11146/llama-b11146-bin-win-cpu-x64.zip`	17.7 MB	MIT	https://github.com/ggml-org/llama.cpp/releases/download/b11146/llama-b11146-bin-win-cpu-x64.zip
`runtime/llama.cpp-b11146/llama-b11146-bin-ubuntu-vulkan-x64.tar.gz`	29.2 MB	MIT	https://github.com/ggml-org/llama.cpp/releases/download/b11146/llama-b11146-bin-ubuntu-vulkan-x64.tar.gz
`runtime/llama.cpp-b11146/llama-b11146-bin-ubuntu-x64.tar.gz`	16.2 MB	MIT	https://github.com/ggml-org/llama.cpp/releases/download/b11146/llama-b11146-bin-ubuntu-x64.tar.gz
`runtime/llama.cpp-b11146/llama-b11146-bin-macos-arm64.tar.gz`	10.7 MB	MIT	https://github.com/ggml-org/llama.cpp/releases/download/b11146/llama-b11146-bin-macos-arm64.tar.gz
`runtime/llama.cpp-b11146/llama-b11146-bin-macos-x64.tar.gz`	10.7 MB	MIT	https://github.com/ggml-org/llama.cpp/releases/download/b11146/llama-b11146-bin-macos-x64.tar.gz
`connectomes/fafb_v783/Supplemental_file1_neuron_annotations.tsv`	30.2 MB	CC-BY 4.0	https://raw.githubusercontent.com/flyconnectome/flywire_annotations/17fc57722002e1a7d38cdd0c89ac382bf92718da/supplemental_files/Supplemental_file1_neuron_annotations.tsv
`connectomes/fafb_v783/proofread_connections_783.feather`	812.6 MB	CC-BY 4.0	https://zenodo.org/api/records/10676866/files/proofread_connections_783.feather/content
`connectomes/malecns_v1.0/body-annotations-male-cns-v1.0-minconf-0.5.feather`	13.8 MB	CC-BY 4.0	https://storage.googleapis.com/flyem-male-cns/v1.0/connectome-data/flat-connectome/body-annotations-male-cns-v1.0-minconf-0.5.feather
`connectomes/malecns_v1.0/body-neurotransmitters-male-cns-v1.0.feather`	41.3 MB	CC-BY 4.0	https://storage.googleapis.com/flyem-male-cns/v1.0/connectome-data/flat-connectome/body-neurotransmitters-male-cns-v1.0.feather
`connectomes/malecns_v1.0/connectome-weights-male-cns-v1.0-minconf-0.5-traced-only.feather`	484.5 MB	CC-BY 4.0	https://storage.googleapis.com/flyem-male-cns/v1.0/connectome-data/flat-connectome/connectome-weights-male-cns-v1.0-minconf-0.5-traced-only.feather
`corpus/everyday_conversations/train_sft.parquet`	2.0 MB	Apache-2.0	https://huggingface.co/datasets/HuggingFaceTB/everyday-conversations-llama3.1-2k/resolve/14f543216b9ba42b6b951dc5bd199460d193b162/data/train_sft-00000-of-00001.parquet
`corpus/everyday_conversations/test_sft.parquet`	0.1 MB	Apache-2.0	https://huggingface.co/datasets/HuggingFaceTB/everyday-conversations-llama3.1-2k/resolve/14f543216b9ba42b6b951dc5bd199460d193b162/data/test_sft-00000-of-00001.parquet
`corpus/dailydialog/train.zip`	1.8 MB	CC-BY-NC-SA-4.0	https://huggingface.co/datasets/roskoN/dailydialog/resolve/5214b2a66405abf87fd229e5c1007985501ffe3e/train.zip
`corpus/dailydialog/validation.zip`	0.2 MB	CC-BY-NC-SA-4.0	https://huggingface.co/datasets/roskoN/dailydialog/resolve/5214b2a66405abf87fd229e5c1007985501ffe3e/validation.zip
`corpus/dailydialog/test.zip`	0.2 MB	CC-BY-NC-SA-4.0	https://huggingface.co/datasets/roskoN/dailydialog/resolve/5214b2a66405abf87fd229e5c1007985501ffe3e/test.zip
`corpus/empathetic_dialogues/empatheticdialogues.tar.gz`	26.7 MB	CC-BY-NC-4.0	https://dl.fbaipublicfiles.com/parlai/empatheticdialogues/empatheticdialogues.tar.gz
`corpus/soda/valid.parquet`	79.0 MB	CC-BY-4.0	https://huggingface.co/datasets/allenai/soda/resolve/fdc848ab0183208ea7808206c91c724414d0a071/valid.parquet
`corpus/oasst1/train.parquet`	37.7 MB	Apache-2.0	https://huggingface.co/datasets/OpenAssistant/oasst1/resolve/fdf72ae0827c1cda404aff25b6603abec9e3399b/data/train-00000-of-00001-b42a775f407cee45.parquet
`corpus/dolly/databricks-dolly-15k.jsonl`	12.5 MB	CC-BY-SA-3.0	https://huggingface.co/datasets/databricks/databricks-dolly-15k/resolve/bdd27f4d94b9c1f951818a7da7fd7aeea5dbff1a/databricks-dolly-15k.jsonl
`corpus/tinystories/validation.parquet`	9.5 MB	CDLA-Sharing-1.0	https://huggingface.co/datasets/roneneldan/TinyStories/resolve/f54c09fd23315a6f9c86f9dc80f725de7d8f9c64/data/validation-00000-of-00001-869c898b519ad725.parquet
`corpus/tinystories/train-00000-of-00004.parquet`	237.2 MB	cdla-sharing-1.0	https://huggingface.co/datasets/roneneldan/TinyStories/resolve/f54c09fd23315a6f9c86f9dc80f725de7d8f9c64/data/train-00000-of-00004-2d5a1467fff1081b.parquet
`brains/flyslm-m-full-thorough-2026-10-04/checkpoint/checkpoint.pt`	134.1 MB	see card.json (connectome CC-BY 4.0; trained on data including non-commercial sources)	trained with FlySLM (run run_flyai_m_full_20261004-154407)
`brains/flyslm-m-full-thorough-2026-10-04/checkpoint/metadata.json`	0.0 MB	see card.json (connectome CC-BY 4.0; trained on data including non-commercial sources)	trained with FlySLM (run run_flyai_m_full_20261004-154407)
`brains/flyslm-m-full-thorough-2026-10-04/tokenizer/provenance.json`	0.0 MB	see card.json (connectome CC-BY 4.0; trained on data including non-commercial sources)	trained with FlySLM (run run_flyai_m_full_20261004-154407)
`brains/flyslm-m-full-thorough-2026-10-04/tokenizer/tokenizer.json`	0.1 MB	see card.json (connectome CC-BY 4.0; trained on data including non-commercial sources)	trained with FlySLM (run run_flyai_m_full_20261004-154407)
`brains/flyslm-m-full-thorough-2026-10-04/package/edges.npz`	20.6 MB	see card.json (connectome CC-BY 4.0; trained on data including non-commercial sources)	trained with FlySLM (run run_flyai_m_full_20261004-154407)
`brains/flyslm-m-full-thorough-2026-10-04/package/manifest.json`	0.0 MB	see card.json (connectome CC-BY 4.0; trained on data including non-commercial sources)	trained with FlySLM (run run_flyai_m_full_20261004-154407)
`brains/flyslm-m-full-thorough-2026-10-04/package/neurons.parquet`	4.8 MB	see card.json (connectome CC-BY 4.0; trained on data including non-commercial sources)	trained with FlySLM (run run_flyai_m_full_20261004-154407)
`brains/flyslm-m-full-thorough-2026-10-04/package/regions.json`	0.0 MB	see card.json (connectome CC-BY 4.0; trained on data including non-commercial sources)	trained with FlySLM (run run_flyai_m_full_20261004-154407)
`brains/flyslm-m-full-thorough-2026-10-04/card.json`	0.0 MB	see card.json (connectome CC-BY 4.0; trained on data including non-commercial sources)	trained with FlySLM (run run_flyai_m_full_20261004-154407)
`brains/flyslm-m-full-thorough-2026-10-04/run.json`	0.1 MB	see card.json (connectome CC-BY 4.0; trained on data including non-commercial sources)	trained with FlySLM (run run_flyai_m_full_20261004-154407)
`brains/flyslm-f-brain-thorough-2026-10-04/checkpoint/checkpoint.pt`	117.2 MB	see card.json (connectome CC-BY 4.0; trained on data including non-commercial sources)	trained with FlySLM (run run_flyai_f_brain_20261004-154452)
`brains/flyslm-f-brain-thorough-2026-10-04/checkpoint/metadata.json`	0.0 MB	see card.json (connectome CC-BY 4.0; trained on data including non-commercial sources)	trained with FlySLM (run run_flyai_f_brain_20261004-154452)
`brains/flyslm-f-brain-thorough-2026-10-04/tokenizer/provenance.json`	0.0 MB	see card.json (connectome CC-BY 4.0; trained on data including non-commercial sources)	trained with FlySLM (run run_flyai_f_brain_20261004-154452)
`brains/flyslm-f-brain-thorough-2026-10-04/tokenizer/tokenizer.json`	0.1 MB	see card.json (connectome CC-BY 4.0; trained on data including non-commercial sources)	trained with FlySLM (run run_flyai_f_brain_20261004-154452)
`brains/flyslm-f-brain-thorough-2026-10-04/package/edges.npz`	9.2 MB	see card.json (connectome CC-BY 4.0; trained on data including non-commercial sources)	trained with FlySLM (run run_flyai_f_brain_20261004-154452)
`brains/flyslm-f-brain-thorough-2026-10-04/package/manifest.json`	0.0 MB	see card.json (connectome CC-BY 4.0; trained on data including non-commercial sources)	trained with FlySLM (run run_flyai_f_brain_20261004-154452)
`brains/flyslm-f-brain-thorough-2026-10-04/package/neurons.parquet`	4.1 MB	see card.json (connectome CC-BY 4.0; trained on data including non-commercial sources)	trained with FlySLM (run run_flyai_f_brain_20261004-154452)
`brains/flyslm-f-brain-thorough-2026-10-04/package/regions.json`	0.1 MB	see card.json (connectome CC-BY 4.0; trained on data including non-commercial sources)	trained with FlySLM (run run_flyai_f_brain_20261004-154452)
`brains/flyslm-f-brain-thorough-2026-10-04/card.json`	0.0 MB	see card.json (connectome CC-BY 4.0; trained on data including non-commercial sources)	trained with FlySLM (run run_flyai_f_brain_20261004-154452)
`brains/flyslm-f-brain-thorough-2026-10-04/run.json`	0.1 MB	see card.json (connectome CC-BY 4.0; trained on data including non-commercial sources)	trained with FlySLM (run run_flyai_f_brain_20261004-154452)

Attribution

Berg S. et al. Sexual dimorphism in the complete connectome of the Drosophila male central nervous system (MaleCNS v1.0, released 2026-06-08; Cell 2026). FlyEM (HHMI Janelia), University of Cambridge, MRC LMB and Google Research. Data: gs://flyem-male-cns/v1.0/.
Conover M. et al. (2023) Free Dolly: Introducing the World's First Truly Open Instruction-Tuned LLM. Databricks.
Dorkenwald S. et al. (2024) Neuronal wiring diagram of an adult brain. Nature 634:124-138. Schlegel P. et al. (2024) Whole-brain annotation and multi-connectome cell typing of Drosophila. Nature 634:139-152. FlyWire Consortium, Zenodo doi:10.5281/zenodo.10676866. Neurotransmitter predictions: Eckstein N., Bates A.S. et al. (2024) Cell 187:2574.
Eldan R., Li Y. (2023) TinyStories. arXiv:2305.07759.
Eldan R., Li Y. (2023) TinyStories. arXiv:2305.07759. Licence CDLA-Sharing-1.0.
HuggingFaceTB/everyday-conversations-llama3.1-2k (synthetic everyday chats generated with Llama 3.1).
Kim H. et al. (2023) SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualization. EMNLP. (allenai/soda)
Köpf A. et al. (2023) OpenAssistant Conversations. NeurIPS Datasets and Benchmarks.
Li Y., Su H., Shen X., Li W., Cao Z., Niu S. (2017) DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset. IJCNLP.
Rashkin H., Smith E. M., Li M., Boureau Y-L. (2019) Towards Empathetic Open-domain Conversation Models. ACL.
Gemma 4 (Google), Apache-2.0. Hy-MT2 (Tencent Hunyuan), Apache-2.0. llama.cpp (ggml-org), MIT.

Downloads last month: 128

Total file size:

10.9 GB

Paper for MateusGSM/FlySLM

TinyStories: How Small Can Language Models Be and Still Speak Coherent English?

Paper • 2305.07759 • Published May 12, 2023 • 50