mlabonne / Model details
NeuralMonarch-7B
mlabonne/NeuralMonarch-7B
Family: Unknown. No supported family evidence recorded.
About this model
Mlabonne's DPO fine-tune of Monarch-7B, distributed as float16 safetensors and intended by its creator for instruction following and reasoning. The repository declares cc-by-nc-4.0. Its card describes an 8k context window; the tokenizer lists 8192 while the model config lists 32768, neither a measured usable-context result here. The card recommends Mistral Instruct, but the bundled tokenizer uses role-labelled formatting, so matching the intended prompt format needs care. Creator-reported benchmarks have not been independently reproduced here.
Description sources
Source-based description, not an independent evaluation. Check the linked sources for the creator’s claims and limitations.
Size and formats
- Base model
- mlabonne/Monarch-7B
- Parameters
- 7.24173B
- Main repository formats
- safetensors
- License tag
- cc-by-nc-4.0
- Languages
- en
- Last updated
- 2024-03-04 · 15:16:59.000 UTC
What changed
Model types are creator-reported, not independently tested. These labels describe source metadata, not a guarantee of behavior.
- fine-tunedsource tag:
base_model:finetune:mlabonne/Monarch-7B
Family evidence
These groupings are source-reported. Explicit base identifiers take priority over generic architecture tags.
- No supported family evidence recorded.
Available versions
Only explicitly linked variants are grouped here. Check the original repository for available files.
- Main repository files ↗safetensors
- No other explicitly linked versions recorded.
Customize or build on this model
Listed from public GitHub data, not tested by us. Read the code and license before you run anything.
Tools to customize it further
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Fine-tune it on your own data
- Unsloth ↗ ★ 78,421
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Make a smaller download (quantize)
- llama.cpp ↗ ★ 132,027
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- MLX LM ↗ ★ 7,435
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Merge it with another model
- mergekit ↗ ★ 7,414
Merges pretrained models with many merge methods. It works out-of-core, so merges can run on a CPU or with as little as 8 GB of VRAM, and it also handles LoRA extraction and mixture-of-experts merges.
Learn the techniques
- LLM Course ↗ ★ 84,598
A free course with roadmaps and Colab notebooks. Its notebooks include one-click tools for merging with MergeKit, quantizing to GGUF, GPTQ, EXL2, AWQ and HQQ, and automatic abliteration with custom datasets.
Source provenance
- Downloads
- 24,606
- Likes
- 12
- Metadata checked
- 2026-10-23 · 01:14:18 UTC
- First seen in index
- 2026-10-23 · 01:14:18 UTC
- Source revision
- bebae99e187a1ab3b009b2736a99a32cdc178c8f
Source-card excerpt
Source model card excerpt: 👑 NeuralMonarch-7B NeuralMonarch-7B is a DPO fine-tuned of mlabonne/Monarch-7B using the jondurbin/truthy-dpo-v0.1 and argilla/distilabel-intel-orca-dpo-pairs preference datasets. It is based on a merge of the
From mlabonne/NeuralMonarch-7B. Creator model-card excerpt, not an independent review.
Inspect before you run
Low refusal is not proof of correctness. Outputs can be inaccurate, harmful, or biased. Review the model card, license and files yourself. A license tag is not commercial-use advice. Parameter counts are source metadata; no hardware compatibility is implied.
This directory does not run, host, redistribute, or test model weights.
Collection rules & limitations ↗