Instructions to use tensorblock/SummLlama3.2-3B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tensorblock/SummLlama3.2-3B-GGUF with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="tensorblock/SummLlama3.2-3B-GGUF") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tensorblock/SummLlama3.2-3B-GGUF", dtype="auto") - llama-cpp-python
How to use tensorblock/SummLlama3.2-3B-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="tensorblock/SummLlama3.2-3B-GGUF", filename="SummLlama3.2-3B-Q2_K.gguf", )
llm.create_chat_completion( messages = "\"The tower is 324 metres (1,063 ft) tall, about the same height as an 81-storey building, and the tallest structure in Paris. Its base is square, measuring 125 metres (410 ft) on each side. During its construction, the Eiffel Tower surpassed the Washington Monument to become the tallest man-made structure in the world, a title it held for 41 years until the Chrysler Building in New York City was finished in 1930. It was the first structure to reach a height of 300 metres. Due to the addition of a broadcasting aerial at the top of the tower in 1957, it is now taller than the Chrysler Building by 5.2 metres (17 ft). Excluding transmitters, the Eiffel Tower is the second tallest free-standing structure in France after the Millau Viaduct.\"" )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use tensorblock/SummLlama3.2-3B-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf tensorblock/SummLlama3.2-3B-GGUF:Q2_K # Run inference directly in the terminal: llama-cli -hf tensorblock/SummLlama3.2-3B-GGUF:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf tensorblock/SummLlama3.2-3B-GGUF:Q2_K # Run inference directly in the terminal: llama-cli -hf tensorblock/SummLlama3.2-3B-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/SummLlama3.2-3B-GGUF:Q2_K # Run inference directly in the terminal: ./llama-cli -hf tensorblock/SummLlama3.2-3B-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/SummLlama3.2-3B-GGUF:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf tensorblock/SummLlama3.2-3B-GGUF:Q2_K
Use Docker
docker model run hf.co/tensorblock/SummLlama3.2-3B-GGUF:Q2_K
- LM Studio
- Jan
- Ollama
How to use tensorblock/SummLlama3.2-3B-GGUF with Ollama:
ollama run hf.co/tensorblock/SummLlama3.2-3B-GGUF:Q2_K
- Unsloth Studio
How to use tensorblock/SummLlama3.2-3B-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/SummLlama3.2-3B-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/SummLlama3.2-3B-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/SummLlama3.2-3B-GGUF to start chatting
- Pi
How to use tensorblock/SummLlama3.2-3B-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf tensorblock/SummLlama3.2-3B-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/SummLlama3.2-3B-GGUF:Q2_K" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use tensorblock/SummLlama3.2-3B-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf tensorblock/SummLlama3.2-3B-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/SummLlama3.2-3B-GGUF:Q2_K
Run Hermes
hermes
- Docker Model Runner
How to use tensorblock/SummLlama3.2-3B-GGUF with Docker Model Runner:
docker model run hf.co/tensorblock/SummLlama3.2-3B-GGUF:Q2_K
- Lemonade
How to use tensorblock/SummLlama3.2-3B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tensorblock/SummLlama3.2-3B-GGUF:Q2_K
Run and chat with the model
lemonade run user.SummLlama3.2-3B-GGUF-Q2_K
List all available models
lemonade list
Upload folder using huggingface_hub
Browse files- .gitattributes +12 -0
- README.md +84 -0
- SummLlama3.2-3B-Q2_K.gguf +3 -0
- SummLlama3.2-3B-Q3_K_L.gguf +3 -0
- SummLlama3.2-3B-Q3_K_M.gguf +3 -0
- SummLlama3.2-3B-Q3_K_S.gguf +3 -0
- SummLlama3.2-3B-Q4_0.gguf +3 -0
- SummLlama3.2-3B-Q4_K_M.gguf +3 -0
- SummLlama3.2-3B-Q4_K_S.gguf +3 -0
- SummLlama3.2-3B-Q5_0.gguf +3 -0
- SummLlama3.2-3B-Q5_K_M.gguf +3 -0
- SummLlama3.2-3B-Q5_K_S.gguf +3 -0
- SummLlama3.2-3B-Q6_K.gguf +3 -0
- SummLlama3.2-3B-Q8_0.gguf +3 -0
.gitattributes
CHANGED
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*.zip filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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SummLlama3.2-3B-Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
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SummLlama3.2-3B-Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
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SummLlama3.2-3B-Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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SummLlama3.2-3B-Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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SummLlama3.2-3B-Q4_0.gguf filter=lfs diff=lfs merge=lfs -text
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SummLlama3.2-3B-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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SummLlama3.2-3B-Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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SummLlama3.2-3B-Q5_0.gguf filter=lfs diff=lfs merge=lfs -text
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SummLlama3.2-3B-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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SummLlama3.2-3B-Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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SummLlama3.2-3B-Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
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SummLlama3.2-3B-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 |
+
library_name: transformers
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| 3 |
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base_model: DISLab/SummLlama3.2-3B
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pipeline_tag: summarization
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tags:
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- TensorBlock
|
| 7 |
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- GGUF
|
| 8 |
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---
|
| 9 |
+
|
| 10 |
+
<div style="width: auto; margin-left: auto; margin-right: auto">
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| 11 |
+
<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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| 13 |
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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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| 15 |
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<p style="margin-top: 0.5em; margin-bottom: 0em;">
|
| 16 |
+
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>
|
| 17 |
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</p>
|
| 18 |
+
</div>
|
| 19 |
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</div>
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| 20 |
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|
| 21 |
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## DISLab/SummLlama3.2-3B - GGUF
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| 22 |
+
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| 23 |
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This repo contains GGUF format model files for [DISLab/SummLlama3.2-3B](https://huggingface.co/DISLab/SummLlama3.2-3B).
|
| 24 |
+
|
| 25 |
+
The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
|
| 26 |
+
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| 27 |
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<div style="text-align: left; margin: 20px 0;">
|
| 28 |
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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;">
|
| 29 |
+
Run them on the TensorBlock client using your local machine ↗
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| 30 |
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</a>
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</div>
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| 32 |
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|
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## Prompt template
|
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```
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| 36 |
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>
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| 37 |
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| 38 |
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Cutting Knowledge Date: December 2023
|
| 39 |
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Today Date: 20 Nov 2024
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| 40 |
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| 41 |
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{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>
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| 42 |
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| 43 |
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{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
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```
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## Model file specification
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| 47 |
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| Filename | Quant type | File Size | Description |
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| 49 |
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| -------- | ---------- | --------- | ----------- |
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| 50 |
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| [SummLlama3.2-3B-Q2_K.gguf](https://huggingface.co/tensorblock/SummLlama3.2-3B-GGUF/blob/main/SummLlama3.2-3B-Q2_K.gguf) | Q2_K | 1.364 GB | smallest, significant quality loss - not recommended for most purposes |
|
| 51 |
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| [SummLlama3.2-3B-Q3_K_S.gguf](https://huggingface.co/tensorblock/SummLlama3.2-3B-GGUF/blob/main/SummLlama3.2-3B-Q3_K_S.gguf) | Q3_K_S | 1.543 GB | very small, high quality loss |
|
| 52 |
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| [SummLlama3.2-3B-Q3_K_M.gguf](https://huggingface.co/tensorblock/SummLlama3.2-3B-GGUF/blob/main/SummLlama3.2-3B-Q3_K_M.gguf) | Q3_K_M | 1.687 GB | very small, high quality loss |
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| [SummLlama3.2-3B-Q3_K_L.gguf](https://huggingface.co/tensorblock/SummLlama3.2-3B-GGUF/blob/main/SummLlama3.2-3B-Q3_K_L.gguf) | Q3_K_L | 1.815 GB | small, substantial quality loss |
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| 54 |
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| [SummLlama3.2-3B-Q4_0.gguf](https://huggingface.co/tensorblock/SummLlama3.2-3B-GGUF/blob/main/SummLlama3.2-3B-Q4_0.gguf) | Q4_0 | 1.917 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
|
| 55 |
+
| [SummLlama3.2-3B-Q4_K_S.gguf](https://huggingface.co/tensorblock/SummLlama3.2-3B-GGUF/blob/main/SummLlama3.2-3B-Q4_K_S.gguf) | Q4_K_S | 1.928 GB | small, greater quality loss |
|
| 56 |
+
| [SummLlama3.2-3B-Q4_K_M.gguf](https://huggingface.co/tensorblock/SummLlama3.2-3B-GGUF/blob/main/SummLlama3.2-3B-Q4_K_M.gguf) | Q4_K_M | 2.019 GB | medium, balanced quality - recommended |
|
| 57 |
+
| [SummLlama3.2-3B-Q5_0.gguf](https://huggingface.co/tensorblock/SummLlama3.2-3B-GGUF/blob/main/SummLlama3.2-3B-Q5_0.gguf) | Q5_0 | 2.270 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
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| 58 |
+
| [SummLlama3.2-3B-Q5_K_S.gguf](https://huggingface.co/tensorblock/SummLlama3.2-3B-GGUF/blob/main/SummLlama3.2-3B-Q5_K_S.gguf) | Q5_K_S | 2.270 GB | large, low quality loss - recommended |
|
| 59 |
+
| [SummLlama3.2-3B-Q5_K_M.gguf](https://huggingface.co/tensorblock/SummLlama3.2-3B-GGUF/blob/main/SummLlama3.2-3B-Q5_K_M.gguf) | Q5_K_M | 2.322 GB | large, very low quality loss - recommended |
|
| 60 |
+
| [SummLlama3.2-3B-Q6_K.gguf](https://huggingface.co/tensorblock/SummLlama3.2-3B-GGUF/blob/main/SummLlama3.2-3B-Q6_K.gguf) | Q6_K | 2.644 GB | very large, extremely low quality loss |
|
| 61 |
+
| [SummLlama3.2-3B-Q8_0.gguf](https://huggingface.co/tensorblock/SummLlama3.2-3B-GGUF/blob/main/SummLlama3.2-3B-Q8_0.gguf) | Q8_0 | 3.422 GB | very large, extremely low quality loss - not recommended |
|
| 62 |
+
|
| 63 |
+
|
| 64 |
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## Downloading instruction
|
| 65 |
+
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| 66 |
+
### Command line
|
| 67 |
+
|
| 68 |
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Firstly, install Huggingface Client
|
| 69 |
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|
| 70 |
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```shell
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| 71 |
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pip install -U "huggingface_hub[cli]"
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| 72 |
+
```
|
| 73 |
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|
| 74 |
+
Then, downoad the individual model file the a local directory
|
| 75 |
+
|
| 76 |
+
```shell
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| 77 |
+
huggingface-cli download tensorblock/SummLlama3.2-3B-GGUF --include "SummLlama3.2-3B-Q2_K.gguf" --local-dir MY_LOCAL_DIR
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| 78 |
+
```
|
| 79 |
+
|
| 80 |
+
If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
|
| 81 |
+
|
| 82 |
+
```shell
|
| 83 |
+
huggingface-cli download tensorblock/SummLlama3.2-3B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
|
| 84 |
+
```
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SummLlama3.2-3B-Q2_K.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:500a9fb0506f4287b8beebfce3cfe0bed299a27440dbbb59289182309f4d7032
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size 1363935552
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SummLlama3.2-3B-Q3_K_L.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:975b706891f13400feba1238cffe4f4ac999c9caebc246a20e43bce4457d85b1
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size 1815347520
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SummLlama3.2-3B-Q3_K_M.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:510a9f757f2891e0272c9575eb6f40e9356f5413636ee5944c9672bef2155324
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size 1687159104
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SummLlama3.2-3B-Q3_K_S.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:c00654c5e25941ad2b1848678b476edb9b7a5108414557924803ebc7e9b6ec1d
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size 1542848832
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SummLlama3.2-3B-Q4_0.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:8fea86b3466bd2322c9aaf1402fa601fcad7c92f1c00567bd46854299d9c9a8f
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+
size 1917190464
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SummLlama3.2-3B-Q4_K_M.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:cbc475fa7daff94c3df64968b626e74481f65222b614cafc0215b6f9b170866a
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| 3 |
+
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