Instructions to use mradermacher/bagel-dpo-7b-v0.5-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mradermacher/bagel-dpo-7b-v0.5-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("mradermacher/bagel-dpo-7b-v0.5-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use mradermacher/bagel-dpo-7b-v0.5-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 mradermacher/bagel-dpo-7b-v0.5-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mradermacher/bagel-dpo-7b-v0.5-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf mradermacher/bagel-dpo-7b-v0.5-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mradermacher/bagel-dpo-7b-v0.5-GGUF:Q4_K_M

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 mradermacher/bagel-dpo-7b-v0.5-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf mradermacher/bagel-dpo-7b-v0.5-GGUF:Q4_K_M

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 mradermacher/bagel-dpo-7b-v0.5-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf mradermacher/bagel-dpo-7b-v0.5-GGUF:Q4_K_M

Use Docker

docker model run hf.co/mradermacher/bagel-dpo-7b-v0.5-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use mradermacher/bagel-dpo-7b-v0.5-GGUF with Ollama:
```
ollama run hf.co/mradermacher/bagel-dpo-7b-v0.5-GGUF:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use mradermacher/bagel-dpo-7b-v0.5-GGUF with Docker Model Runner:
```
docker model run hf.co/mradermacher/bagel-dpo-7b-v0.5-GGUF:Q4_K_M
```

Lemonade

How to use mradermacher/bagel-dpo-7b-v0.5-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull mradermacher/bagel-dpo-7b-v0.5-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.bagel-dpo-7b-v0.5-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

mradermacher commited on Dec 17, 2024

Commit

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@@ -1,6 +1,106 @@
 <!-- ### quantize_version: 2 -->
 <!-- ### output_tensor_quantised: 1 -->
 <!-- ### convert_type: hf -->
 <!-- ### vocab_type:  -->
 <!-- ### tags:  -->
 static quants of https://huggingface.co/jondurbin/bagel-dpo-7b-v0.5

+---
+base_model: jondurbin/bagel-dpo-7b-v0.5
+datasets:
+- ai2_arc
+- allenai/ultrafeedback_binarized_cleaned
+- argilla/distilabel-intel-orca-dpo-pairs
+- jondurbin/airoboros-3.2
+- codeparrot/apps
+- facebook/belebele
+- bluemoon-fandom-1-1-rp-cleaned
+- boolq
+- camel-ai/biology
+- camel-ai/chemistry
+- camel-ai/math
+- camel-ai/physics
+- jondurbin/contextual-dpo-v0.1
+- jondurbin/gutenberg-dpo-v0.1
+- jondurbin/py-dpo-v0.1
+- jondurbin/truthy-dpo-v0.1
+- LDJnr/Capybara
+- jondurbin/cinematika-v0.1
+- WizardLM/WizardLM_evol_instruct_70k
+- glaiveai/glaive-function-calling-v2
+- jondurbin/gutenberg-dpo-v0.1
+- grimulkan/LimaRP-augmented
+- lmsys/lmsys-chat-1m
+- ParisNeo/lollms_aware_dataset
+- TIGER-Lab/MathInstruct
+- Muennighoff/natural-instructions
+- openbookqa
+- kingbri/PIPPA-shareGPT
+- piqa
+- Vezora/Tested-22k-Python-Alpaca
+- ropes
+- cakiki/rosetta-code
+- Open-Orca/SlimOrca
+- b-mc2/sql-create-context
+- squad_v2
+- mattpscott/airoboros-summarization
+- migtissera/Synthia-v1.3
+- unalignment/toxic-dpo-v0.2
+- WhiteRabbitNeo/WRN-Chapter-1
+- WhiteRabbitNeo/WRN-Chapter-2
+- winogrande
+language:
+- en
+library_name: transformers
+license: apache-2.0
+quantized_by: mradermacher
+---
+## About
 <!-- ### quantize_version: 2 -->
 <!-- ### output_tensor_quantised: 1 -->
 <!-- ### convert_type: hf -->
 <!-- ### vocab_type:  -->
 <!-- ### tags:  -->
 static quants of https://huggingface.co/jondurbin/bagel-dpo-7b-v0.5
+<!-- provided-files -->
+weighted/imatrix quants are available at https://huggingface.co/mradermacher/bagel-dpo-7b-v0.5-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/bagel-dpo-7b-v0.5-GGUF/resolve/main/bagel-dpo-7b-v0.5.Q2_K.gguf) | Q2_K | 2.8 |  |
+| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.5-GGUF/resolve/main/bagel-dpo-7b-v0.5.Q3_K_S.gguf) | Q3_K_S | 3.3 |  |
+| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.5-GGUF/resolve/main/bagel-dpo-7b-v0.5.Q3_K_M.gguf) | Q3_K_M | 3.6 | lower quality |
+| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.5-GGUF/resolve/main/bagel-dpo-7b-v0.5.Q3_K_L.gguf) | Q3_K_L | 3.9 |  |
+| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.5-GGUF/resolve/main/bagel-dpo-7b-v0.5.IQ4_XS.gguf) | IQ4_XS | 4.0 |  |
+| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.5-GGUF/resolve/main/bagel-dpo-7b-v0.5.Q4_K_S.gguf) | Q4_K_S | 4.2 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.5-GGUF/resolve/main/bagel-dpo-7b-v0.5.Q4_K_M.gguf) | Q4_K_M | 4.5 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.5-GGUF/resolve/main/bagel-dpo-7b-v0.5.Q5_K_S.gguf) | Q5_K_S | 5.1 |  |
+| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.5-GGUF/resolve/main/bagel-dpo-7b-v0.5.Q5_K_M.gguf) | Q5_K_M | 5.2 |  |
+| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.5-GGUF/resolve/main/bagel-dpo-7b-v0.5.Q6_K.gguf) | Q6_K | 6.0 | very good quality |
+| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.5-GGUF/resolve/main/bagel-dpo-7b-v0.5.Q8_0.gguf) | Q8_0 | 7.8 | fast, best quality |
+| [GGUF](https://huggingface.co/mradermacher/bagel-dpo-7b-v0.5-GGUF/resolve/main/bagel-dpo-7b-v0.5.f16.gguf) | f16 | 14.6 | 16 bpw, overkill |
+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.
+<!-- end -->