Instructions to use tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use tensorblock/Qwen2.5-7B-MixStock-V0.1-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 tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF:Q2_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 tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF:Q2_K # Run inference directly in the terminal: ./llama-cli -hf tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF:Q2_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 tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF:Q2_K
Use Docker
docker model run hf.co/tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF:Q2_K
- LM Studio
- Jan
- Ollama
How to use tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF with Ollama:
ollama run hf.co/tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF:Q2_K
- Unsloth Studio
How to use tensorblock/Qwen2.5-7B-MixStock-V0.1-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 tensorblock/Qwen2.5-7B-MixStock-V0.1-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 tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF to start chatting
- Pi
How to use tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF:Q2_K
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF:Q2_K" } ] } } }Run Pi
# Start Pi in your project directory: pi
- OpenClaw new
How to use tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF:Q2_K
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF:Q2_K" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
- Docker Model Runner
How to use tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF with Docker Model Runner:
docker model run hf.co/tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF:Q2_K
- Lemonade
How to use tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF:Q2_K
Run and chat with the model
lemonade run user.Qwen2.5-7B-MixStock-V0.1-GGUF-Q2_K
List all available models
lemonade list
- Hermes Agent
How to use tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF:Q2_K
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF:Q2_K
Run Hermes
hermes
- Atomic Chat
Upload folder using huggingface_hub
Browse files- .gitattributes +12 -0
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- README.md +177 -0
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README.md
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| 1 |
+
---
|
| 2 |
+
library_name: transformers
|
| 3 |
+
tags:
|
| 4 |
+
- mergekit
|
| 5 |
+
- merge
|
| 6 |
+
- TensorBlock
|
| 7 |
+
- GGUF
|
| 8 |
+
base_model: bunnycore/Qwen2.5-7B-MixStock-V0.1
|
| 9 |
+
model-index:
|
| 10 |
+
- name: Qwen2.5-7B-MixStock-V0.1
|
| 11 |
+
results:
|
| 12 |
+
- task:
|
| 13 |
+
type: text-generation
|
| 14 |
+
name: Text Generation
|
| 15 |
+
dataset:
|
| 16 |
+
name: IFEval (0-Shot)
|
| 17 |
+
type: HuggingFaceH4/ifeval
|
| 18 |
+
args:
|
| 19 |
+
num_few_shot: 0
|
| 20 |
+
metrics:
|
| 21 |
+
- type: inst_level_strict_acc and prompt_level_strict_acc
|
| 22 |
+
value: 76.73
|
| 23 |
+
name: strict accuracy
|
| 24 |
+
source:
|
| 25 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-MixStock-V0.1
|
| 26 |
+
name: Open LLM Leaderboard
|
| 27 |
+
- task:
|
| 28 |
+
type: text-generation
|
| 29 |
+
name: Text Generation
|
| 30 |
+
dataset:
|
| 31 |
+
name: BBH (3-Shot)
|
| 32 |
+
type: BBH
|
| 33 |
+
args:
|
| 34 |
+
num_few_shot: 3
|
| 35 |
+
metrics:
|
| 36 |
+
- type: acc_norm
|
| 37 |
+
value: 35.87
|
| 38 |
+
name: normalized accuracy
|
| 39 |
+
source:
|
| 40 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-MixStock-V0.1
|
| 41 |
+
name: Open LLM Leaderboard
|
| 42 |
+
- task:
|
| 43 |
+
type: text-generation
|
| 44 |
+
name: Text Generation
|
| 45 |
+
dataset:
|
| 46 |
+
name: MATH Lvl 5 (4-Shot)
|
| 47 |
+
type: hendrycks/competition_math
|
| 48 |
+
args:
|
| 49 |
+
num_few_shot: 4
|
| 50 |
+
metrics:
|
| 51 |
+
- type: exact_match
|
| 52 |
+
value: 28.85
|
| 53 |
+
name: exact match
|
| 54 |
+
source:
|
| 55 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-MixStock-V0.1
|
| 56 |
+
name: Open LLM Leaderboard
|
| 57 |
+
- task:
|
| 58 |
+
type: text-generation
|
| 59 |
+
name: Text Generation
|
| 60 |
+
dataset:
|
| 61 |
+
name: GPQA (0-shot)
|
| 62 |
+
type: Idavidrein/gpqa
|
| 63 |
+
args:
|
| 64 |
+
num_few_shot: 0
|
| 65 |
+
metrics:
|
| 66 |
+
- type: acc_norm
|
| 67 |
+
value: 6.71
|
| 68 |
+
name: acc_norm
|
| 69 |
+
source:
|
| 70 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-MixStock-V0.1
|
| 71 |
+
name: Open LLM Leaderboard
|
| 72 |
+
- task:
|
| 73 |
+
type: text-generation
|
| 74 |
+
name: Text Generation
|
| 75 |
+
dataset:
|
| 76 |
+
name: MuSR (0-shot)
|
| 77 |
+
type: TAUR-Lab/MuSR
|
| 78 |
+
args:
|
| 79 |
+
num_few_shot: 0
|
| 80 |
+
metrics:
|
| 81 |
+
- type: acc_norm
|
| 82 |
+
value: 14.9
|
| 83 |
+
name: acc_norm
|
| 84 |
+
source:
|
| 85 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-MixStock-V0.1
|
| 86 |
+
name: Open LLM Leaderboard
|
| 87 |
+
- task:
|
| 88 |
+
type: text-generation
|
| 89 |
+
name: Text Generation
|
| 90 |
+
dataset:
|
| 91 |
+
name: MMLU-PRO (5-shot)
|
| 92 |
+
type: TIGER-Lab/MMLU-Pro
|
| 93 |
+
config: main
|
| 94 |
+
split: test
|
| 95 |
+
args:
|
| 96 |
+
num_few_shot: 5
|
| 97 |
+
metrics:
|
| 98 |
+
- type: acc
|
| 99 |
+
value: 36.18
|
| 100 |
+
name: accuracy
|
| 101 |
+
source:
|
| 102 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-MixStock-V0.1
|
| 103 |
+
name: Open LLM Leaderboard
|
| 104 |
+
---
|
| 105 |
+
|
| 106 |
+
<div style="width: auto; margin-left: auto; margin-right: auto">
|
| 107 |
+
<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
|
| 108 |
+
</div>
|
| 109 |
+
<div style="display: flex; justify-content: space-between; width: 100%;">
|
| 110 |
+
<div style="display: flex; flex-direction: column; align-items: flex-start;">
|
| 111 |
+
<p style="margin-top: 0.5em; margin-bottom: 0em;">
|
| 112 |
+
Feedback and support: TensorBlock's <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a>
|
| 113 |
+
</p>
|
| 114 |
+
</div>
|
| 115 |
+
</div>
|
| 116 |
+
|
| 117 |
+
## bunnycore/Qwen2.5-7B-MixStock-V0.1 - GGUF
|
| 118 |
+
|
| 119 |
+
This repo contains GGUF format model files for [bunnycore/Qwen2.5-7B-MixStock-V0.1](https://huggingface.co/bunnycore/Qwen2.5-7B-MixStock-V0.1).
|
| 120 |
+
|
| 121 |
+
The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4823](https://github.com/ggml-org/llama.cpp/commit/5bbe6a9fe9a8796a9389c85accec89dbc4d91e39).
|
| 122 |
+
|
| 123 |
+
<div style="text-align: left; margin: 20px 0;">
|
| 124 |
+
<a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
|
| 125 |
+
Run them on the TensorBlock client using your local machine ↗
|
| 126 |
+
</a>
|
| 127 |
+
</div>
|
| 128 |
+
|
| 129 |
+
## Prompt template
|
| 130 |
+
|
| 131 |
+
```
|
| 132 |
+
<|im_start|>system
|
| 133 |
+
{system_prompt}<|im_end|>
|
| 134 |
+
<|im_start|>user
|
| 135 |
+
{prompt}<|im_end|>
|
| 136 |
+
<|im_start|>assistant
|
| 137 |
+
```
|
| 138 |
+
|
| 139 |
+
## Model file specification
|
| 140 |
+
|
| 141 |
+
| Filename | Quant type | File Size | Description |
|
| 142 |
+
| -------- | ---------- | --------- | ----------- |
|
| 143 |
+
| [Qwen2.5-7B-MixStock-V0.1-Q2_K.gguf](https://huggingface.co/tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF/blob/main/Qwen2.5-7B-MixStock-V0.1-Q2_K.gguf) | Q2_K | 3.014 GB | smallest, significant quality loss - not recommended for most purposes |
|
| 144 |
+
| [Qwen2.5-7B-MixStock-V0.1-Q3_K_S.gguf](https://huggingface.co/tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF/blob/main/Qwen2.5-7B-MixStock-V0.1-Q3_K_S.gguf) | Q3_K_S | 3.491 GB | very small, high quality loss |
|
| 145 |
+
| [Qwen2.5-7B-MixStock-V0.1-Q3_K_M.gguf](https://huggingface.co/tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF/blob/main/Qwen2.5-7B-MixStock-V0.1-Q3_K_M.gguf) | Q3_K_M | 3.807 GB | very small, high quality loss |
|
| 146 |
+
| [Qwen2.5-7B-MixStock-V0.1-Q3_K_L.gguf](https://huggingface.co/tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF/blob/main/Qwen2.5-7B-MixStock-V0.1-Q3_K_L.gguf) | Q3_K_L | 4.087 GB | small, substantial quality loss |
|
| 147 |
+
| [Qwen2.5-7B-MixStock-V0.1-Q4_0.gguf](https://huggingface.co/tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF/blob/main/Qwen2.5-7B-MixStock-V0.1-Q4_0.gguf) | Q4_0 | 4.429 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
|
| 148 |
+
| [Qwen2.5-7B-MixStock-V0.1-Q4_K_S.gguf](https://huggingface.co/tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF/blob/main/Qwen2.5-7B-MixStock-V0.1-Q4_K_S.gguf) | Q4_K_S | 4.456 GB | small, greater quality loss |
|
| 149 |
+
| [Qwen2.5-7B-MixStock-V0.1-Q4_K_M.gguf](https://huggingface.co/tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF/blob/main/Qwen2.5-7B-MixStock-V0.1-Q4_K_M.gguf) | Q4_K_M | 4.681 GB | medium, balanced quality - recommended |
|
| 150 |
+
| [Qwen2.5-7B-MixStock-V0.1-Q5_0.gguf](https://huggingface.co/tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF/blob/main/Qwen2.5-7B-MixStock-V0.1-Q5_0.gguf) | Q5_0 | 5.313 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
|
| 151 |
+
| [Qwen2.5-7B-MixStock-V0.1-Q5_K_S.gguf](https://huggingface.co/tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF/blob/main/Qwen2.5-7B-MixStock-V0.1-Q5_K_S.gguf) | Q5_K_S | 5.313 GB | large, low quality loss - recommended |
|
| 152 |
+
| [Qwen2.5-7B-MixStock-V0.1-Q5_K_M.gguf](https://huggingface.co/tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF/blob/main/Qwen2.5-7B-MixStock-V0.1-Q5_K_M.gguf) | Q5_K_M | 5.443 GB | large, very low quality loss - recommended |
|
| 153 |
+
| [Qwen2.5-7B-MixStock-V0.1-Q6_K.gguf](https://huggingface.co/tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF/blob/main/Qwen2.5-7B-MixStock-V0.1-Q6_K.gguf) | Q6_K | 6.252 GB | very large, extremely low quality loss |
|
| 154 |
+
| [Qwen2.5-7B-MixStock-V0.1-Q8_0.gguf](https://huggingface.co/tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF/blob/main/Qwen2.5-7B-MixStock-V0.1-Q8_0.gguf) | Q8_0 | 8.095 GB | very large, extremely low quality loss - not recommended |
|
| 155 |
+
|
| 156 |
+
|
| 157 |
+
## Downloading instruction
|
| 158 |
+
|
| 159 |
+
### Command line
|
| 160 |
+
|
| 161 |
+
Firstly, install Huggingface Client
|
| 162 |
+
|
| 163 |
+
```shell
|
| 164 |
+
pip install -U "huggingface_hub[cli]"
|
| 165 |
+
```
|
| 166 |
+
|
| 167 |
+
Then, downoad the individual model file the a local directory
|
| 168 |
+
|
| 169 |
+
```shell
|
| 170 |
+
huggingface-cli download tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF --include "Qwen2.5-7B-MixStock-V0.1-Q2_K.gguf" --local-dir MY_LOCAL_DIR
|
| 171 |
+
```
|
| 172 |
+
|
| 173 |
+
If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
|
| 174 |
+
|
| 175 |
+
```shell
|
| 176 |
+
huggingface-cli download tensorblock/Qwen2.5-7B-MixStock-V0.1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
|
| 177 |
+
```
|