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5ak3t

Models in Library5
Datasets in Library0
Models on Hugging Face4
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Compare the published evidence

This profile connects the 5 model and dataset records shown below to their upstream cards and sources. The library counts describe SAVRN's coverage, rather than this publisher's entire output.

Published tasks: Text classification.

Reported licenses: other. Open a record to review its specific license and conditions.

Compare model specifications, source dates, and hardware estimates on the individual records. Publisher identity verification is separate from a model's quality, deployment readiness, or suitability for your work.

Models

Model · Text classification

scm-max-14b-v0

Takes

SCM ("Sovereign Classification Model", repository rev) makes typed, non-generative decisions in one forward pass: choice (pick one of K), noul (yes/no) and score (ordinal level) questions about a state. This repo holds a LoRA adapter only (adaptermodel.safetensors) for Qwen/Qwen3-14B-Base at revision 0b0bd3732e2c374d483664439ea334928b65f304. It is an experimental research release, not a production model. All options of one question are shown in one prompt as lettered lines; the model's score for an option is the next-token logit of its letter. Several option orders are scored and their per-order log-softmax over the letters is averaged, then renormalised to a probability vector. The exact…

Open weights other peft

Model · Text classification

scm-min-1.7b-v0

Takes

SCM ("Sovereign Classification Model", repository rev) makes typed, non-generative decisions in one forward pass: choice (pick one of K), noul (yes/no) and score (ordinal level) questions about a state. This repo holds a LoRA adapter only (adaptermodel.safetensors) for Qwen/Qwen3-1.7B-Base at revision ea980cb0a6c2ae4b936e82123acc929f1cec04c1. It is an experimental research release, not a production model. All options of one question are shown in one prompt as lettered lines; the model's score for an option is the next-token logit of its letter. Several option orders are scored and their per-order log-softmax over the letters is averaged, then renormalised to a probability vector. The exact…

Open weights other peft

Model · Text classification

scm-mid-4b-v0

Takes

SCM ("Sovereign Classification Model", repository rev) makes typed, non-generative decisions in one forward pass: choice (pick one of K), noul (yes/no) and score (ordinal level) questions about a state. This repo holds a LoRA adapter only (adaptermodel.safetensors) for Qwen/Qwen3-4B-Base at revision 906504ac4b72e133a613011318afd8206fb5e8ec. It is an experimental research release, not a production model. All options of one question are shown in one prompt as lettered lines; the model's score for an option is the next-token logit of its letter. Several option orders are scored and their per-order log-softmax over the letters is averaged, then renormalised to a probability vector. The exact…

Open weights other peft

Model · Text classification

scm-mid-4b-v1

Takes

SCM ("Sovereign Classification Model") makes typed decisions in one forward pass: choice (pick one of K), noul (yes/no) and score (ordinal level) questions about a text. This repo holds a LoRA adapter only for Qwen/Qwen3-4B-Base at revision 906bfd4b4dc7f14ee4320094d8b41684abff8539 (training run s88-v1mid-H100-20261015-113727; lr 1e-4 (fp16, 1 GPU), LoRA r=16 / alpha=32 on all attention and MLP projections, 16 questions per step, one epoch, prompts left-truncated at 3,072 tokens). It is not a production model. All options of one question appear in one prompt as labelled lines; the score of an option is the next-token logit of its label. Labels are A to T, then U to Z, then single-token…

Open weights other peft

Model · Text classification

scm-max-14b-v1

Takes

SCM ("Sovereign Classification Model") makes typed decisions in one forward pass: choice (pick one of K), noul (yes/no) and score (ordinal level) questions about a text. This repo holds a LoRA adapter only for Qwen/Qwen3-14B-Base at revision 0b0bd3732e2c374d483664439ea334928b65f304 (training run s88-v1max-H100x2-20261015-113714; lr 5e-5 (bf16, 2 GPUs data-parallel), LoRA r=16 / alpha=32 on all attention and MLP projections, 16 questions per step, one epoch, prompts left-truncated at 3,072 tokens). It is not a production model. All options of one question appear in one prompt as labelled lines; the score of an option is the next-token logit of its label. Labels are A to T, then U to Z, then…

Open weights other peft