Dolphin3.0-R1-Mistral-24B-GGUF

Instructions to use lactroiii/Dolphin3.0-R1-Mistral-24B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use lactroiii/Dolphin3.0-R1-Mistral-24B-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("lactroiii/Dolphin3.0-R1-Mistral-24B-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use lactroiii/Dolphin3.0-R1-Mistral-24B-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf lactroiii/Dolphin3.0-R1-Mistral-24B-GGUF:Q6_K
# Run inference directly in the terminal:
llama cli -hf lactroiii/Dolphin3.0-R1-Mistral-24B-GGUF:Q6_K

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf lactroiii/Dolphin3.0-R1-Mistral-24B-GGUF:Q6_K
# Run inference directly in the terminal:
llama cli -hf lactroiii/Dolphin3.0-R1-Mistral-24B-GGUF:Q6_K

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf lactroiii/Dolphin3.0-R1-Mistral-24B-GGUF:Q6_K
# Run inference directly in the terminal:
./llama-cli -hf lactroiii/Dolphin3.0-R1-Mistral-24B-GGUF:Q6_K

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf lactroiii/Dolphin3.0-R1-Mistral-24B-GGUF:Q6_K
# Run inference directly in the terminal:
./build/bin/llama-cli -hf lactroiii/Dolphin3.0-R1-Mistral-24B-GGUF:Q6_K

Use Docker

docker model run hf.co/lactroiii/Dolphin3.0-R1-Mistral-24B-GGUF:Q6_K

LM Studio
Jan
Ollama
How to use lactroiii/Dolphin3.0-R1-Mistral-24B-GGUF with Ollama:
```
ollama run hf.co/lactroiii/Dolphin3.0-R1-Mistral-24B-GGUF:Q6_K
```

Unsloth Studio

How to use lactroiii/Dolphin3.0-R1-Mistral-24B-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for lactroiii/Dolphin3.0-R1-Mistral-24B-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for lactroiii/Dolphin3.0-R1-Mistral-24B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for lactroiii/Dolphin3.0-R1-Mistral-24B-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use lactroiii/Dolphin3.0-R1-Mistral-24B-GGUF with Docker Model Runner:
```
docker model run hf.co/lactroiii/Dolphin3.0-R1-Mistral-24B-GGUF:Q6_K
```

Lemonade

How to use lactroiii/Dolphin3.0-R1-Mistral-24B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull lactroiii/Dolphin3.0-R1-Mistral-24B-GGUF:Q6_K

Run and chat with the model

lemonade run user.Dolphin3.0-R1-Mistral-24B-GGUF-Q6_K

List all available models

lemonade list

lactroiii

mradermacher commited on Apr 7

Commit

44f336f

0 Parent(s):

Duplicate from mradermacher/Dolphin3.0-R1-Mistral-24B-GGUF

Browse files

Co-authored-by: team mradermacher <mradermacher@users.noreply.huggingface.co>

Files changed (4) hide show

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+---
+base_model: dphn/Dolphin3.0-R1-Mistral-24B
+datasets:
+- cognitivecomputations/dolphin-r1
+- OpenCoder-LLM/opc-sft-stage1
+- OpenCoder-LLM/opc-sft-stage2
+- microsoft/orca-agentinstruct-1M-v1
+- microsoft/orca-math-word-problems-200k
+- NousResearch/hermes-function-calling-v1
+- AI-MO/NuminaMath-CoT
+- AI-MO/NuminaMath-TIR
+- allenai/tulu-3-sft-mixture
+- cognitivecomputations/dolphin-coder
+- HuggingFaceTB/smoltalk
+- cognitivecomputations/samantha-data
+- m-a-p/CodeFeedback-Filtered-Instruction
+- m-a-p/Code-Feedback
+language:
+- en
+library_name: transformers
+mradermacher:
+  readme_rev: 1
+quantized_by: mradermacher
+---
+## About
+<!-- ### quantize_version: 2 -->
+<!-- ### output_tensor_quantised: 1 -->
+<!-- ### convert_type: hf -->
+<!-- ### vocab_type:  -->
+<!-- ### tags: nicoboss -->
+static quants of https://huggingface.co/dphn/Dolphin3.0-R1-Mistral-24B
+<!-- provided-files -->
+***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Dolphin3.0-R1-Mistral-24B-GGUF).***
+weighted/imatrix quants are available at https://huggingface.co/mradermacher/Dolphin3.0-R1-Mistral-24B-i1-GGUF
+## Usage
+If you are unsure how to use GGUF files, refer to one of [TheBloke's
+READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
+more details, including on how to concatenate multi-part files.
+## Provided Quants
+(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
+| Link | Type | Size/GB | Notes |
+|:-----|:-----|--------:|:------|
+| [GGUF](https://huggingface.co/mradermacher/Dolphin3.0-R1-Mistral-24B-GGUF/resolve/main/Dolphin3.0-R1-Mistral-24B.Q2_K.gguf) | Q2_K | 9.0 |  |
+| [GGUF](https://huggingface.co/mradermacher/Dolphin3.0-R1-Mistral-24B-GGUF/resolve/main/Dolphin3.0-R1-Mistral-24B.Q3_K_S.gguf) | Q3_K_S | 10.5 |  |
+| [GGUF](https://huggingface.co/mradermacher/Dolphin3.0-R1-Mistral-24B-GGUF/resolve/main/Dolphin3.0-R1-Mistral-24B.Q3_K_M.gguf) | Q3_K_M | 11.6 | lower quality |
+| [GGUF](https://huggingface.co/mradermacher/Dolphin3.0-R1-Mistral-24B-GGUF/resolve/main/Dolphin3.0-R1-Mistral-24B.Q3_K_L.gguf) | Q3_K_L | 12.5 |  |
+| [GGUF](https://huggingface.co/mradermacher/Dolphin3.0-R1-Mistral-24B-GGUF/resolve/main/Dolphin3.0-R1-Mistral-24B.IQ4_XS.gguf) | IQ4_XS | 13.0 |  |
+| [GGUF](https://huggingface.co/mradermacher/Dolphin3.0-R1-Mistral-24B-GGUF/resolve/main/Dolphin3.0-R1-Mistral-24B.Q4_K_S.gguf) | Q4_K_S | 13.6 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/Dolphin3.0-R1-Mistral-24B-GGUF/resolve/main/Dolphin3.0-R1-Mistral-24B.Q4_K_M.gguf) | Q4_K_M | 14.4 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/Dolphin3.0-R1-Mistral-24B-GGUF/resolve/main/Dolphin3.0-R1-Mistral-24B.Q5_K_S.gguf) | Q5_K_S | 16.4 |  |
+| [GGUF](https://huggingface.co/mradermacher/Dolphin3.0-R1-Mistral-24B-GGUF/resolve/main/Dolphin3.0-R1-Mistral-24B.Q5_K_M.gguf) | Q5_K_M | 16.9 |  |
+| [GGUF](https://huggingface.co/mradermacher/Dolphin3.0-R1-Mistral-24B-GGUF/resolve/main/Dolphin3.0-R1-Mistral-24B.Q6_K.gguf) | Q6_K | 19.4 | very good quality |
+| [GGUF](https://huggingface.co/mradermacher/Dolphin3.0-R1-Mistral-24B-GGUF/resolve/main/Dolphin3.0-R1-Mistral-24B.Q8_0.gguf) | Q8_0 | 25.2 | fast, best quality |
+Here is a handy graph by ikawrakow comparing some lower-quality quant
+types (lower is better):
+![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
+And here are Artefact2's thoughts on the matter:
+https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
+## FAQ / Model Request
+See https://huggingface.co/mradermacher/model_requests for some answers to
+questions you might have and/or if you want some other model quantized.
+## Thanks
+I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
+me use its servers and providing upgrades to my workstation to enable
+this work in my free time. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.
+<!-- end -->