Instructions to use tensorblock/MiniCPM3-4B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use tensorblock/MiniCPM3-4B-GGUF with Transformers:

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

pipe = pipeline("text-generation", model="tensorblock/MiniCPM3-4B-GGUF")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("tensorblock/MiniCPM3-4B-GGUF", dtype="auto")

llama-cpp-python

How to use tensorblock/MiniCPM3-4B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="tensorblock/MiniCPM3-4B-GGUF",
	filename="MiniCPM3-4B-Q2_K.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use tensorblock/MiniCPM3-4B-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/MiniCPM3-4B-GGUF:Q2_K
# Run inference directly in the terminal:
llama-cli -hf tensorblock/MiniCPM3-4B-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/MiniCPM3-4B-GGUF:Q2_K
# Run inference directly in the terminal:
llama-cli -hf tensorblock/MiniCPM3-4B-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/MiniCPM3-4B-GGUF:Q2_K
# Run inference directly in the terminal:
./llama-cli -hf tensorblock/MiniCPM3-4B-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/MiniCPM3-4B-GGUF:Q2_K
# Run inference directly in the terminal:
./build/bin/llama-cli -hf tensorblock/MiniCPM3-4B-GGUF:Q2_K

Use Docker

docker model run hf.co/tensorblock/MiniCPM3-4B-GGUF:Q2_K

LM Studio
Jan

vLLM

How to use tensorblock/MiniCPM3-4B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "tensorblock/MiniCPM3-4B-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/MiniCPM3-4B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/tensorblock/MiniCPM3-4B-GGUF:Q2_K

SGLang

How to use tensorblock/MiniCPM3-4B-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/MiniCPM3-4B-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/MiniCPM3-4B-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/MiniCPM3-4B-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/MiniCPM3-4B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use tensorblock/MiniCPM3-4B-GGUF with Ollama:
```
ollama run hf.co/tensorblock/MiniCPM3-4B-GGUF:Q2_K
```

Unsloth Studio

How to use tensorblock/MiniCPM3-4B-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/MiniCPM3-4B-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/MiniCPM3-4B-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/MiniCPM3-4B-GGUF to start chatting

How to use tensorblock/MiniCPM3-4B-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/MiniCPM3-4B-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/MiniCPM3-4B-GGUF:Q2_K"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use tensorblock/MiniCPM3-4B-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/MiniCPM3-4B-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/MiniCPM3-4B-GGUF:Q2_K

Run Hermes

hermes

Docker Model Runner
How to use tensorblock/MiniCPM3-4B-GGUF with Docker Model Runner:
```
docker model run hf.co/tensorblock/MiniCPM3-4B-GGUF:Q2_K
```

Lemonade

How to use tensorblock/MiniCPM3-4B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull tensorblock/MiniCPM3-4B-GGUF:Q2_K

Run and chat with the model

lemonade run user.MiniCPM3-4B-GGUF-Q2_K

List all available models

lemonade list

morriszms commited on Nov 29, 2024

Commit

70821d3

verified ·

1 Parent(s): b80bc87

Upload folder using huggingface_hub

Browse files

Files changed (14) hide show

.gitattributes +12 -0
MiniCPM3-4B-Q2_K.gguf +3 -0
MiniCPM3-4B-Q3_K_L.gguf +3 -0
MiniCPM3-4B-Q3_K_M.gguf +3 -0
MiniCPM3-4B-Q3_K_S.gguf +3 -0
MiniCPM3-4B-Q4_0.gguf +3 -0
MiniCPM3-4B-Q4_K_M.gguf +3 -0
MiniCPM3-4B-Q4_K_S.gguf +3 -0
MiniCPM3-4B-Q5_0.gguf +3 -0
MiniCPM3-4B-Q5_K_M.gguf +3 -0
MiniCPM3-4B-Q5_K_S.gguf +3 -0
MiniCPM3-4B-Q6_K.gguf +3 -0
MiniCPM3-4B-Q8_0.gguf +3 -0
README.md +85 -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
+MiniCPM3-4B-Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
+MiniCPM3-4B-Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
+MiniCPM3-4B-Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+MiniCPM3-4B-Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+MiniCPM3-4B-Q4_0.gguf filter=lfs diff=lfs merge=lfs -text
+MiniCPM3-4B-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+MiniCPM3-4B-Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+MiniCPM3-4B-Q5_0.gguf filter=lfs diff=lfs merge=lfs -text
+MiniCPM3-4B-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+MiniCPM3-4B-Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+MiniCPM3-4B-Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
+MiniCPM3-4B-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text

MiniCPM3-4B-Q2_K.gguf ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:bfa728c555c6b9ec77f30b2f5e549f3566004fbdbfa174946585a96586e2e5a0
+size 1576858368

MiniCPM3-4B-Q3_K_L.gguf ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:72d636cd6af8656b1119dfdf73c31b193b645cc9bff10a468192f1725aae7087
+size 2193683968

MiniCPM3-4B-Q3_K_M.gguf ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:bed761aa3cbe804f8f3e17443dda53f10da3e907fedc664cbf41f715f00b7ee6
+size 2022061568

MiniCPM3-4B-Q3_K_S.gguf ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:77a8f38c27b902c2f23edad72719f8bcfd1714f560fa21e959ae7c4dd7857287
+size 1827040768

MiniCPM3-4B-Q4_0.gguf ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:e6cc3714407deec3772c92c5923101667b969c764fa475fe450c48e0f954ae30
+size 2343079168

MiniCPM3-4B-Q4_K_M.gguf ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:3b41585e395bb79cb4270601cdbd4c6a6d26e53d0fcacfd9cd4cb34aff900c4b
+size 2469799168

MiniCPM3-4B-Q4_K_S.gguf ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:5aa96b6ddce15211e37d2b75d52632314ca5367772a4e1ed944b4f4cc4f5b840
+size 2357415168

MiniCPM3-4B-Q5_0.gguf ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:a0d31ba7408158d440e8050ef66b5e0ce018fa121ab038e4f9c0378946dd37d8
+size 2828762368

MiniCPM3-4B-Q5_K_M.gguf ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:90c52151a0e2a50ff1c57c96e94fd69eea1f94d3a768993b6c40311ed9f284ce
+size 2894042368

MiniCPM3-4B-Q5_K_S.gguf ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:1647a93df366979305aa694f7163f2d1ef7bb06072ba413de30d8f8c671264cb
+size 2828762368

MiniCPM3-4B-Q6_K.gguf ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:37f46797c32ccf67b8e87d948af26d1ceda176c4bdead36f54273d45677a1521
+size 3344800768

MiniCPM3-4B-Q8_0.gguf ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:46b1c81f6e3919d6db1395b2c968b21e19e87f51a22c5105218258d2061af794
+size 4331349728

README.md ADDED Viewed

	@@ -0,0 +1,85 @@

+---
+license: apache-2.0
+language:
+- zh
+- en
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- TensorBlock
+- GGUF
+base_model: openbmb/MiniCPM3-4B
+---
+<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>
+## openbmb/MiniCPM3-4B - GGUF
+This repo contains GGUF format model files for [openbmb/MiniCPM3-4B](https://huggingface.co/openbmb/MiniCPM3-4B).
+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).
+<div style="text-align: left; margin: 20px 0;">
+    <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;">
+        Run them on the TensorBlock client using your local machine ↗
+    </a>
+</div>
+## 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 |
+| -------- | ---------- | --------- | ----------- |
+| [MiniCPM3-4B-Q2_K.gguf](https://huggingface.co/tensorblock/MiniCPM3-4B-GGUF/blob/main/MiniCPM3-4B-Q2_K.gguf) | Q2_K | 1.577 GB | smallest, significant quality loss - not recommended for most purposes |
+| [MiniCPM3-4B-Q3_K_S.gguf](https://huggingface.co/tensorblock/MiniCPM3-4B-GGUF/blob/main/MiniCPM3-4B-Q3_K_S.gguf) | Q3_K_S | 1.827 GB | very small, high quality loss |
+| [MiniCPM3-4B-Q3_K_M.gguf](https://huggingface.co/tensorblock/MiniCPM3-4B-GGUF/blob/main/MiniCPM3-4B-Q3_K_M.gguf) | Q3_K_M | 2.022 GB | very small, high quality loss |
+| [MiniCPM3-4B-Q3_K_L.gguf](https://huggingface.co/tensorblock/MiniCPM3-4B-GGUF/blob/main/MiniCPM3-4B-Q3_K_L.gguf) | Q3_K_L | 2.194 GB | small, substantial quality loss |
+| [MiniCPM3-4B-Q4_0.gguf](https://huggingface.co/tensorblock/MiniCPM3-4B-GGUF/blob/main/MiniCPM3-4B-Q4_0.gguf) | Q4_0 | 2.343 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
+| [MiniCPM3-4B-Q4_K_S.gguf](https://huggingface.co/tensorblock/MiniCPM3-4B-GGUF/blob/main/MiniCPM3-4B-Q4_K_S.gguf) | Q4_K_S | 2.357 GB | small, greater quality loss |
+| [MiniCPM3-4B-Q4_K_M.gguf](https://huggingface.co/tensorblock/MiniCPM3-4B-GGUF/blob/main/MiniCPM3-4B-Q4_K_M.gguf) | Q4_K_M | 2.470 GB | medium, balanced quality - recommended |
+| [MiniCPM3-4B-Q5_0.gguf](https://huggingface.co/tensorblock/MiniCPM3-4B-GGUF/blob/main/MiniCPM3-4B-Q5_0.gguf) | Q5_0 | 2.829 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
+| [MiniCPM3-4B-Q5_K_S.gguf](https://huggingface.co/tensorblock/MiniCPM3-4B-GGUF/blob/main/MiniCPM3-4B-Q5_K_S.gguf) | Q5_K_S | 2.829 GB | large, low quality loss - recommended |
+| [MiniCPM3-4B-Q5_K_M.gguf](https://huggingface.co/tensorblock/MiniCPM3-4B-GGUF/blob/main/MiniCPM3-4B-Q5_K_M.gguf) | Q5_K_M | 2.894 GB | large, very low quality loss - recommended |
+| [MiniCPM3-4B-Q6_K.gguf](https://huggingface.co/tensorblock/MiniCPM3-4B-GGUF/blob/main/MiniCPM3-4B-Q6_K.gguf) | Q6_K | 3.345 GB | very large, extremely low quality loss |
+| [MiniCPM3-4B-Q8_0.gguf](https://huggingface.co/tensorblock/MiniCPM3-4B-GGUF/blob/main/MiniCPM3-4B-Q8_0.gguf) | Q8_0 | 4.331 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/MiniCPM3-4B-GGUF --include "MiniCPM3-4B-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/MiniCPM3-4B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
+```