Text Generation
GGUF
English
Vietnamese
Chinese
vllm
system-role
langchain
TensorBlock
GGUF
conversational
Instructions to use tensorblock/gemma-2-9b-it-fix-system-role-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use tensorblock/gemma-2-9b-it-fix-system-role-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/gemma-2-9b-it-fix-system-role-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/gemma-2-9b-it-fix-system-role-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/gemma-2-9b-it-fix-system-role-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/gemma-2-9b-it-fix-system-role-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/gemma-2-9b-it-fix-system-role-GGUF:Q2_K # Run inference directly in the terminal: ./llama-cli -hf tensorblock/gemma-2-9b-it-fix-system-role-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/gemma-2-9b-it-fix-system-role-GGUF:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf tensorblock/gemma-2-9b-it-fix-system-role-GGUF:Q2_K
Use Docker
docker model run hf.co/tensorblock/gemma-2-9b-it-fix-system-role-GGUF:Q2_K
- LM Studio
- Jan
- vLLM
How to use tensorblock/gemma-2-9b-it-fix-system-role-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "tensorblock/gemma-2-9b-it-fix-system-role-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tensorblock/gemma-2-9b-it-fix-system-role-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/tensorblock/gemma-2-9b-it-fix-system-role-GGUF:Q2_K
- Ollama
How to use tensorblock/gemma-2-9b-it-fix-system-role-GGUF with Ollama:
ollama run hf.co/tensorblock/gemma-2-9b-it-fix-system-role-GGUF:Q2_K
- Unsloth Studio
How to use tensorblock/gemma-2-9b-it-fix-system-role-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/gemma-2-9b-it-fix-system-role-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/gemma-2-9b-it-fix-system-role-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/gemma-2-9b-it-fix-system-role-GGUF to start chatting
- Docker Model Runner
How to use tensorblock/gemma-2-9b-it-fix-system-role-GGUF with Docker Model Runner:
docker model run hf.co/tensorblock/gemma-2-9b-it-fix-system-role-GGUF:Q2_K
- Lemonade
How to use tensorblock/gemma-2-9b-it-fix-system-role-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tensorblock/gemma-2-9b-it-fix-system-role-GGUF:Q2_K
Run and chat with the model
lemonade run user.gemma-2-9b-it-fix-system-role-GGUF-Q2_K
List all available models
lemonade list
- Atomic Chat
Upload folder using huggingface_hub
Browse files- .gitattributes +12 -0
- README.md +87 -0
- gemma-2-9b-it-fix-system-role-Q2_K.gguf +3 -0
- gemma-2-9b-it-fix-system-role-Q3_K_L.gguf +3 -0
- gemma-2-9b-it-fix-system-role-Q3_K_M.gguf +3 -0
- gemma-2-9b-it-fix-system-role-Q3_K_S.gguf +3 -0
- gemma-2-9b-it-fix-system-role-Q4_0.gguf +3 -0
- gemma-2-9b-it-fix-system-role-Q4_K_M.gguf +3 -0
- gemma-2-9b-it-fix-system-role-Q4_K_S.gguf +3 -0
- gemma-2-9b-it-fix-system-role-Q5_0.gguf +3 -0
- gemma-2-9b-it-fix-system-role-Q5_K_M.gguf +3 -0
- gemma-2-9b-it-fix-system-role-Q5_K_S.gguf +3 -0
- gemma-2-9b-it-fix-system-role-Q6_K.gguf +3 -0
- gemma-2-9b-it-fix-system-role-Q8_0.gguf +3 -0
.gitattributes
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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gemma-2-9b-it-fix-system-role-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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gemma-2-9b-it-fix-system-role-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
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README.md
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| 1 |
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---
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| 2 |
+
language:
|
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- en
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| 4 |
+
- vi
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| 5 |
+
- zh
|
| 6 |
+
base_model: dangvansam/gemma-2-9b-it-fix-system-role
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| 7 |
+
pipeline_tag: text-generation
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| 8 |
+
tags:
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| 9 |
+
- vllm
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| 10 |
+
- system-role
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| 11 |
+
- langchain
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| 12 |
+
- TensorBlock
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| 13 |
+
- GGUF
|
| 14 |
+
license: gemma
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| 15 |
+
---
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| 16 |
+
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| 17 |
+
<div style="width: auto; margin-left: auto; margin-right: auto">
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<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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</div>
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<div style="display: flex; justify-content: space-between; width: 100%;">
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<div style="display: flex; flex-direction: column; align-items: flex-start;">
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| 22 |
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<p style="margin-top: 0.5em; margin-bottom: 0em;">
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| 23 |
+
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>
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| 24 |
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</p>
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</div>
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| 26 |
+
</div>
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| 28 |
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## dangvansam/gemma-2-9b-it-fix-system-role - GGUF
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This repo contains GGUF format model files for [dangvansam/gemma-2-9b-it-fix-system-role](https://huggingface.co/dangvansam/gemma-2-9b-it-fix-system-role).
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+
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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).
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<div style="text-align: left; margin: 20px 0;">
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<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;">
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| 36 |
+
Run them on the TensorBlock client using your local machine ↗
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</a>
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</div>
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## Prompt template
|
| 41 |
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```
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| 43 |
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<bos>{system_prompt}
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| 44 |
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<start_of_turn>user
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| 45 |
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{prompt}<end_of_turn>
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<start_of_turn>model
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| 47 |
+
```
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## Model file specification
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| 50 |
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| Filename | Quant type | File Size | Description |
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| 52 |
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| -------- | ---------- | --------- | ----------- |
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| 53 |
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| [gemma-2-9b-it-fix-system-role-Q2_K.gguf](https://huggingface.co/tensorblock/gemma-2-9b-it-fix-system-role-GGUF/blob/main/gemma-2-9b-it-fix-system-role-Q2_K.gguf) | Q2_K | 3.805 GB | smallest, significant quality loss - not recommended for most purposes |
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| 54 |
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| [gemma-2-9b-it-fix-system-role-Q3_K_S.gguf](https://huggingface.co/tensorblock/gemma-2-9b-it-fix-system-role-GGUF/blob/main/gemma-2-9b-it-fix-system-role-Q3_K_S.gguf) | Q3_K_S | 4.338 GB | very small, high quality loss |
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| 55 |
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| [gemma-2-9b-it-fix-system-role-Q3_K_M.gguf](https://huggingface.co/tensorblock/gemma-2-9b-it-fix-system-role-GGUF/blob/main/gemma-2-9b-it-fix-system-role-Q3_K_M.gguf) | Q3_K_M | 4.762 GB | very small, high quality loss |
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| 56 |
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| [gemma-2-9b-it-fix-system-role-Q3_K_L.gguf](https://huggingface.co/tensorblock/gemma-2-9b-it-fix-system-role-GGUF/blob/main/gemma-2-9b-it-fix-system-role-Q3_K_L.gguf) | Q3_K_L | 5.132 GB | small, substantial quality loss |
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| 57 |
+
| [gemma-2-9b-it-fix-system-role-Q4_0.gguf](https://huggingface.co/tensorblock/gemma-2-9b-it-fix-system-role-GGUF/blob/main/gemma-2-9b-it-fix-system-role-Q4_0.gguf) | Q4_0 | 5.443 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
|
| 58 |
+
| [gemma-2-9b-it-fix-system-role-Q4_K_S.gguf](https://huggingface.co/tensorblock/gemma-2-9b-it-fix-system-role-GGUF/blob/main/gemma-2-9b-it-fix-system-role-Q4_K_S.gguf) | Q4_K_S | 5.479 GB | small, greater quality loss |
|
| 59 |
+
| [gemma-2-9b-it-fix-system-role-Q4_K_M.gguf](https://huggingface.co/tensorblock/gemma-2-9b-it-fix-system-role-GGUF/blob/main/gemma-2-9b-it-fix-system-role-Q4_K_M.gguf) | Q4_K_M | 5.761 GB | medium, balanced quality - recommended |
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| 60 |
+
| [gemma-2-9b-it-fix-system-role-Q5_0.gguf](https://huggingface.co/tensorblock/gemma-2-9b-it-fix-system-role-GGUF/blob/main/gemma-2-9b-it-fix-system-role-Q5_0.gguf) | Q5_0 | 6.484 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
|
| 61 |
+
| [gemma-2-9b-it-fix-system-role-Q5_K_S.gguf](https://huggingface.co/tensorblock/gemma-2-9b-it-fix-system-role-GGUF/blob/main/gemma-2-9b-it-fix-system-role-Q5_K_S.gguf) | Q5_K_S | 6.484 GB | large, low quality loss - recommended |
|
| 62 |
+
| [gemma-2-9b-it-fix-system-role-Q5_K_M.gguf](https://huggingface.co/tensorblock/gemma-2-9b-it-fix-system-role-GGUF/blob/main/gemma-2-9b-it-fix-system-role-Q5_K_M.gguf) | Q5_K_M | 6.647 GB | large, very low quality loss - recommended |
|
| 63 |
+
| [gemma-2-9b-it-fix-system-role-Q6_K.gguf](https://huggingface.co/tensorblock/gemma-2-9b-it-fix-system-role-GGUF/blob/main/gemma-2-9b-it-fix-system-role-Q6_K.gguf) | Q6_K | 7.589 GB | very large, extremely low quality loss |
|
| 64 |
+
| [gemma-2-9b-it-fix-system-role-Q8_0.gguf](https://huggingface.co/tensorblock/gemma-2-9b-it-fix-system-role-GGUF/blob/main/gemma-2-9b-it-fix-system-role-Q8_0.gguf) | Q8_0 | 9.827 GB | very large, extremely low quality loss - not recommended |
|
| 65 |
+
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| 66 |
+
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| 67 |
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## Downloading instruction
|
| 68 |
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| 69 |
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### Command line
|
| 70 |
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| 71 |
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Firstly, install Huggingface Client
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| 72 |
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| 73 |
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```shell
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| 74 |
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pip install -U "huggingface_hub[cli]"
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| 75 |
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```
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| 76 |
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Then, downoad the individual model file the a local directory
|
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| 79 |
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```shell
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| 80 |
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huggingface-cli download tensorblock/gemma-2-9b-it-fix-system-role-GGUF --include "gemma-2-9b-it-fix-system-role-Q2_K.gguf" --local-dir MY_LOCAL_DIR
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| 81 |
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```
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| 82 |
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| 83 |
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If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
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| 84 |
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| 85 |
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```shell
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| 86 |
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huggingface-cli download tensorblock/gemma-2-9b-it-fix-system-role-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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| 87 |
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```
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