dphn / Model details
Dolphin-Mistral-24B-Venice-Edition
dphn/Dolphin-Mistral-24B-Venice-Edition
About this model
A Mistral Small 24B Instruct fine-tune made by Dolphin with Venice. The creators describe it as uncensored and emphasize setting your own system prompt. The card recommends a low temperature, such as 0.15. This repository provides the canonical safetensors checkpoint rather than an FP8 or GGUF package. The creator's setup advice and claims about refusal behavior have not been tested 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
- mistralai/Mistral-Small-24B-Instruct-2501
- Parameters
- 24.0114B
- Main repository formats
- safetensors
- License tag
- apache-2.0
- Languages
- Unknown
- Last updated
- 2026-06-12 · 09:16:02.000 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:mistralai/Mistral-Small-24B-Instruct-2501
Family evidence
These groupings are source-reported. Explicit base identifiers take priority over generic architecture tags.
- Mistral / Mixtral: Base model: mistralai/Mistral-Small-24B-Instruct-2501
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
Remove more refusals
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- OBLITERATUS ↗ ★ 8,917
A larger refusal-removal toolkit with several abliteration methods, usable locally or through a hosted Hugging Face Space. Check the telemetry setting before you run it: the README describes telemetry as opt-in, but on by default in the Spaces version.
Fine-tune it on your own data
- Unsloth ↗ ★ 78,421
A desktop app and Python library for running and training models locally. Its README lists LoRA, QLoRA, full fine-tuning, DPO and GRPO, plus export to formats including GGUF, on Windows, Linux, WSL and macOS.
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Make a smaller download (quantize)
- llama.cpp ↗ ★ 132,027
Runs models locally and includes the tools behind most GGUF files. A conversion script turns Hugging Face weights into GGUF, and llama-quantize shrinks a high-precision GGUF to lower-bit formats, which can cost some accuracy.
- MLX LM ↗ ★ 7,435
Apple's MLX package for running and fine-tuning models on Apple silicon. It can quantize models and upload them to the Hugging Face Hub, and supports LoRA and full fine-tuning.
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
- 7,734
- Likes
- 759
- Metadata checked
- 2026-10-22 · 22:41:08 UTC
- First seen in index
- 2026-10-22 · 22:41:08 UTC
- Source revision
- b23ff40b4a25e4f93de432bd896d4464479a9f79
Source-card excerpt
Source model card excerpt: 🐬 Dolphin Mistral 24B Venice Edition 🌅 Website: Twitter: Web Chat: Telegram bot: This model was trained on 8xB200 provided by What is Dolphin
From dphn/Dolphin-Mistral-24B-Venice-Edition. 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 ↗