Instructions to use tensorblock/Qwen2.5-Coder-1.5B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use tensorblock/Qwen2.5-Coder-1.5B-GGUF with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="tensorblock/Qwen2.5-Coder-1.5B-GGUF")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("tensorblock/Qwen2.5-Coder-1.5B-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use tensorblock/Qwen2.5-Coder-1.5B-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-Coder-1.5B-GGUF:Q2_K
# Run inference directly in the terminal:
llama cli -hf tensorblock/Qwen2.5-Coder-1.5B-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-Coder-1.5B-GGUF:Q2_K
# Run inference directly in the terminal:
llama cli -hf tensorblock/Qwen2.5-Coder-1.5B-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-Coder-1.5B-GGUF:Q2_K
# Run inference directly in the terminal:
./llama-cli -hf tensorblock/Qwen2.5-Coder-1.5B-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-Coder-1.5B-GGUF:Q2_K
# Run inference directly in the terminal:
./build/bin/llama-cli -hf tensorblock/Qwen2.5-Coder-1.5B-GGUF:Q2_K

Use Docker

docker model run hf.co/tensorblock/Qwen2.5-Coder-1.5B-GGUF:Q2_K

LM Studio
Jan

vLLM

How to use tensorblock/Qwen2.5-Coder-1.5B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "tensorblock/Qwen2.5-Coder-1.5B-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/Qwen2.5-Coder-1.5B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/tensorblock/Qwen2.5-Coder-1.5B-GGUF:Q2_K

SGLang

How to use tensorblock/Qwen2.5-Coder-1.5B-GGUF with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "tensorblock/Qwen2.5-Coder-1.5B-GGUF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tensorblock/Qwen2.5-Coder-1.5B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "tensorblock/Qwen2.5-Coder-1.5B-GGUF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tensorblock/Qwen2.5-Coder-1.5B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use tensorblock/Qwen2.5-Coder-1.5B-GGUF with Ollama:
```
ollama run hf.co/tensorblock/Qwen2.5-Coder-1.5B-GGUF:Q2_K
```
Unsloth Desktop

How to use tensorblock/Qwen2.5-Coder-1.5B-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-Coder-1.5B-GGUF:Q2_K

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/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-Coder-1.5B-GGUF:Q2_K"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use tensorblock/Qwen2.5-Coder-1.5B-GGUF with Docker Model Runner:
```
docker model run hf.co/tensorblock/Qwen2.5-Coder-1.5B-GGUF:Q2_K
```

Lemonade

How to use tensorblock/Qwen2.5-Coder-1.5B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull tensorblock/Qwen2.5-Coder-1.5B-GGUF:Q2_K

Run and chat with the model

lemonade run user.Qwen2.5-Coder-1.5B-GGUF-Q2_K

List all available models

lemonade list

Hermes Agent

How to use tensorblock/Qwen2.5-Coder-1.5B-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-Coder-1.5B-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-Coder-1.5B-GGUF:Q2_K

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use tensorblock/Qwen2.5-Coder-1.5B-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-Coder-1.5B-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-Coder-1.5B-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"

morriszms commited on Nov 10, 2024

Commit

56be89b

verified ·

1 Parent(s): 0e162f7

Upload folder using huggingface_hub

Browse files

Files changed (14) hide show

.gitattributes +12 -0
Qwen2.5-Coder-1.5B-Q2_K.gguf +3 -0
Qwen2.5-Coder-1.5B-Q3_K_L.gguf +3 -0
Qwen2.5-Coder-1.5B-Q3_K_M.gguf +3 -0
Qwen2.5-Coder-1.5B-Q3_K_S.gguf +3 -0
Qwen2.5-Coder-1.5B-Q4_0.gguf +3 -0
Qwen2.5-Coder-1.5B-Q4_K_M.gguf +3 -0
Qwen2.5-Coder-1.5B-Q4_K_S.gguf +3 -0
Qwen2.5-Coder-1.5B-Q5_0.gguf +3 -0
Qwen2.5-Coder-1.5B-Q5_K_M.gguf +3 -0
Qwen2.5-Coder-1.5B-Q5_K_S.gguf +3 -0
Qwen2.5-Coder-1.5B-Q6_K.gguf +3 -0
Qwen2.5-Coder-1.5B-Q8_0.gguf +3 -0
README.md +83 -0

.gitattributes CHANGED Viewed

@@ -33,3 +33,15 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text

 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+Qwen2.5-Coder-1.5B-Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2.5-Coder-1.5B-Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2.5-Coder-1.5B-Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2.5-Coder-1.5B-Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2.5-Coder-1.5B-Q4_0.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2.5-Coder-1.5B-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2.5-Coder-1.5B-Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2.5-Coder-1.5B-Q5_0.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2.5-Coder-1.5B-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2.5-Coder-1.5B-Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2.5-Coder-1.5B-Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2.5-Coder-1.5B-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text

Qwen2.5-Coder-1.5B-Q2_K.gguf ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:026d7208b1573c64779c09ba9c6f798a584432c619666f0a2f23caa2b045acdf
+size 676304896

Qwen2.5-Coder-1.5B-Q3_K_L.gguf ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:c4f35e1cba7b9db10a844cbc28ab2bd3c5d24c8a6651671f8bfc7c5720d862ed
+size 880162816

Qwen2.5-Coder-1.5B-Q3_K_M.gguf ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:bfbd9bb9a4866e6bcb816519352953194700da776f7983210570768058ed0228
+size 824178688

Qwen2.5-Coder-1.5B-Q3_K_S.gguf ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:88e3680fd440a0e6f1d073f43a385931cb54fed36a887ce2659e3037cc6aea5b
+size 760944640

Qwen2.5-Coder-1.5B-Q4_0.gguf ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:e2dd6f9eb6a5828c4c99777574b9dbc2dd675c5e8138b4c89623a202bb7f9784
+size 934955008

Qwen2.5-Coder-1.5B-Q4_K_M.gguf ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:3ccaae0f0c8b3d1d51e1338a9bc2dad6d6d93bfd89269624df4ba9a1b918f6f8
+size 986048512

Qwen2.5-Coder-1.5B-Q4_K_S.gguf ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:975b84fac4830f614294799f4fdd94264b6467cbd86640b31c4ade09df883109
+size 940312576

Qwen2.5-Coder-1.5B-Q5_0.gguf ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:3406cd3b2a1f7217b58aea78456ac08163950eb9fcb714e582452a23a96f536d
+size 1098729472

Qwen2.5-Coder-1.5B-Q5_K_M.gguf ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:e7d0c6e8477c6f821cc7c282c9d76aee938b73cb24410b59c2546fa29207a4fa
+size 1125050368

Qwen2.5-Coder-1.5B-Q5_K_S.gguf ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:b2e021c4ed2cea1dddbf7e1828d804903ea5770377fcd0903d88bcd5c99b6029
+size 1098729472

Qwen2.5-Coder-1.5B-Q6_K.gguf ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:1d18a10b09541dd66bdcc2ff9a050b63c4ea8f1be761ec999f23742c3edac0cb
+size 1272739840

Qwen2.5-Coder-1.5B-Q8_0.gguf ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:1f6158a7075af0f3148af9c91f2d86b5e80557b55ffd417653fc1a2bc198d4b0
+size 1646573056

README.md ADDED Viewed

	@@ -0,0 +1,83 @@

+---
+license: apache-2.0
+license_link: https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B/blob/main/LICENSE
+language:
+- en
+base_model: Qwen/Qwen2.5-Coder-1.5B
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- code
+- qwen
+- qwen-coder
+- codeqwen
+- TensorBlock
+- GGUF
+---
+<div style="width: auto; margin-left: auto; margin-right: auto">
+<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
+</div>
+<div style="display: flex; justify-content: space-between; width: 100%;">
+    <div style="display: flex; flex-direction: column; align-items: flex-start;">
+        <p style="margin-top: 0.5em; margin-bottom: 0em;">
+            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>
+        </p>
+    </div>
+</div>
+## Qwen/Qwen2.5-Coder-1.5B - GGUF
+This repo contains GGUF format model files for [Qwen/Qwen2.5-Coder-1.5B](https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B).
+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).
+## Prompt template
+```
+<|im_start|>system
+{system_prompt}<|im_end|>
+<|im_start|>user
+{prompt}<|im_end|>
+<|im_start|>assistant
+```
+## Model file specification
+| Filename | Quant type | File Size | Description |
+| -------- | ---------- | --------- | ----------- |
+| [Qwen2.5-Coder-1.5B-Q2_K.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-GGUF/tree/main/Qwen2.5-Coder-1.5B-Q2_K.gguf) | Q2_K | 0.630 GB | smallest, significant quality loss - not recommended for most purposes |
+| [Qwen2.5-Coder-1.5B-Q3_K_S.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-GGUF/tree/main/Qwen2.5-Coder-1.5B-Q3_K_S.gguf) | Q3_K_S | 0.709 GB | very small, high quality loss |
+| [Qwen2.5-Coder-1.5B-Q3_K_M.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-GGUF/tree/main/Qwen2.5-Coder-1.5B-Q3_K_M.gguf) | Q3_K_M | 0.768 GB | very small, high quality loss |
+| [Qwen2.5-Coder-1.5B-Q3_K_L.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-GGUF/tree/main/Qwen2.5-Coder-1.5B-Q3_K_L.gguf) | Q3_K_L | 0.820 GB | small, substantial quality loss |
+| [Qwen2.5-Coder-1.5B-Q4_0.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-GGUF/tree/main/Qwen2.5-Coder-1.5B-Q4_0.gguf) | Q4_0 | 0.871 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
+| [Qwen2.5-Coder-1.5B-Q4_K_S.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-GGUF/tree/main/Qwen2.5-Coder-1.5B-Q4_K_S.gguf) | Q4_K_S | 0.876 GB | small, greater quality loss |
+| [Qwen2.5-Coder-1.5B-Q4_K_M.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-GGUF/tree/main/Qwen2.5-Coder-1.5B-Q4_K_M.gguf) | Q4_K_M | 0.918 GB | medium, balanced quality - recommended |
+| [Qwen2.5-Coder-1.5B-Q5_0.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-GGUF/tree/main/Qwen2.5-Coder-1.5B-Q5_0.gguf) | Q5_0 | 1.023 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
+| [Qwen2.5-Coder-1.5B-Q5_K_S.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-GGUF/tree/main/Qwen2.5-Coder-1.5B-Q5_K_S.gguf) | Q5_K_S | 1.023 GB | large, low quality loss - recommended |
+| [Qwen2.5-Coder-1.5B-Q5_K_M.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-GGUF/tree/main/Qwen2.5-Coder-1.5B-Q5_K_M.gguf) | Q5_K_M | 1.048 GB | large, very low quality loss - recommended |
+| [Qwen2.5-Coder-1.5B-Q6_K.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-GGUF/tree/main/Qwen2.5-Coder-1.5B-Q6_K.gguf) | Q6_K | 1.185 GB | very large, extremely low quality loss |
+| [Qwen2.5-Coder-1.5B-Q8_0.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-GGUF/tree/main/Qwen2.5-Coder-1.5B-Q8_0.gguf) | Q8_0 | 1.533 GB | very large, extremely low quality loss - not recommended |
+## Downloading instruction
+### Command line
+Firstly, install Huggingface Client
+```shell
+pip install -U "huggingface_hub[cli]"
+```
+Then, downoad the individual model file the a local directory
+```shell
+huggingface-cli download tensorblock/Qwen2.5-Coder-1.5B-GGUF --include "Qwen2.5-Coder-1.5B-Q2_K.gguf" --local-dir MY_LOCAL_DIR
+```
+If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
+```shell
+huggingface-cli download tensorblock/Qwen2.5-Coder-1.5B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
+```