datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
carbon-cpu-enriched-sequences
carbon-cpu-enriched-sequences
A CPU-enriched subset of the carbon pretraining corpus (eukaryote_generator), combining original source fields with normalized sequences
and row-level features for quality analysis, GPU enrichment and embedding generation.
Information of Features
Feature
Type
Description
record_id
string
NCBI Identifier linking the row back to the source genomic record. It provides the primary record-level identity.
begin_of_sequence… See the full description on the dataset page: https://huggingface.co/datasets/AINovice2005/carbon-cpu-enriched-sequences.qwen3-5-tiny-cpu-repro-v1
Qwen3.5 tiny native random CPU fixture
Complete randomly initialized, untrained Qwen3_5ForConditionalGeneration checkpoint.
This is a pipeline/reproducibility fixture, not a useful language model, distillation,
quantization, quality benchmark, or claim about the performance of Qwen3.8-27B.
No upstream model weights or training data were used. No paid GPU/cloud compute.
Architecture and lineage
Architecture lineage: Qwen/Qwen3.8-27B at… See the full description on the dataset page: https://huggingface.co/datasets/malaiwah/qwen3-5-tiny-cpu-repro-v1.glm5-next-tiny-cpu-repro-v1This repository is an evidence bundle, not one root-format dataset at repository root.
first/ and repeat/ are separate complete sealed QFS root datasets; comparison/ holds
the comparison receipt and tokenwise result. panel/ is the sealed input panel. Other files
are provenance, logs and reproduction tools. Do not pass the bundle root as a QFS dataset.
GLM5-Next tiny native CPU fixture
This is a complete untrained random-initialized native Glm5NextForConditionalGeneration
wrapper… See the full description on the dataset page: https://huggingface.co/datasets/malaiwah/glm5-next-tiny-cpu-repro-v1.k2-horizon-tiny-cpu-repro-v1
K2-Horizon MoVA tiny random CPU fixture
Complete untrained K2HorizonForCausalLM, not Moonshot Kimi despite the K2 name.
Architecture source: IFM/K2-Horizon-MoVA-36B-A4B at 05cab0a4d7150c1c460a000b37ff40cc1af2feaa.
No pretrained weights, original tokenizer, training data, paid GPU or cloud compute used.
Complete text-only K2HorizonForCausalLM, not Kimi: three-layer dense prefix followed by two real MoVA+MoE layers, grouped RMSNorm, sigmoid top-k routing with selection-only bias… See the full description on the dataset page: https://huggingface.co/datasets/malaiwah/k2-horizon-tiny-cpu-repro-v1.deepseek-v4-tiny-cpu-repro-v1
DeepSeek-V4 tiny corrected-native-primitives CPU text fixture
Complete randomly initialized, untrained QFSDeepseekV4ForCausalLM text class
using Transformers5.16.1 native primitives and a reviewed RMSNorm arithmetic correction.
No upstream weights, paid GPU/cloud compute or useful-model claim.
This is not unmodified native Transformers or the complete production release.
Architecture and scope
Text lineage:… See the full description on the dataset page: https://huggingface.co/datasets/malaiwah/deepseek-v4-tiny-cpu-repro-v1.minimax-m3-tiny-cpu-repro-v1
minimax-m3 complete native tiny random CPU fixture
Complete untrained MiniMaxM3SparseForConditionalGeneration checkpoint with an untied full LM head,
a real 272-entry byte tokenizer and every native state tensor. Architecture lineage:
MiniMaxAI/MiniMax-M3@f0e1c1e04d40177e4673a22097036854f536e9c0.
No upstream weights, training data, paid GPU or cloud compute were used.
Complete native image/text wrapper with real shrunk Conv3D vision, nonempty 3D RoPE, patch-merge projector and… See the full description on the dataset page: https://huggingface.co/datasets/malaiwah/minimax-m3-tiny-cpu-repro-v1.minimax-m2-tiny-cpu-repro-v1
minimax-m2 complete native tiny random CPU fixture
Complete untrained MiniMaxM2ForCausalLM checkpoint with an untied full LM head,
a real 272-entry byte tokenizer and every native state tensor. Architecture lineage:
MiniMaxAI/MiniMax-M2.7@d494266a4affc0d2995ba1fa35c8481cbd84294b.
No upstream weights, training data, paid GPU or cloud compute were used.
Complete native text causal LM: sigmoid/top-k MoE routing with correction bias, per-layer flattened Q/K RMSNorm and half-head… See the full description on the dataset page: https://huggingface.co/datasets/malaiwah/minimax-m2-tiny-cpu-repro-v1.