Instructions to use ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF with Transformers:

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

pipe = pipeline("text-generation", model="ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-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 ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF:Q5_0
# Run inference directly in the terminal:
llama cli -hf ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF:Q5_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF:Q5_0
# Run inference directly in the terminal:
llama cli -hf ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF:Q5_0

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 ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF:Q5_0
# Run inference directly in the terminal:
./llama-cli -hf ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF:Q5_0

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 ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF:Q5_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF:Q5_0

Use Docker

docker model run hf.co/ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF:Q5_0

LM Studio
Jan

vLLM

How to use ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF:Q5_0

SGLang

How to use ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-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 "ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Ollama
How to use ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF with Ollama:
```
ollama run hf.co/ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF:Q5_0
```
Unsloth Desktop
Docker Model Runner
How to use ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF with Docker Model Runner:
```
docker model run hf.co/ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF:Q5_0
```

Lemonade

How to use ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF:Q5_0

Run and chat with the model

lemonade run user.L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF-Q5_0

List all available models

lemonade list

Atomic Chat

ZeroXClem commited on Nov 21, 2024

Commit

67f80a8

verified ·

1 Parent(s): b7184ed

Update README.md

Browse files

Files changed (1) hide show

README.md +8 -8

README.md CHANGED Viewed

@@ -11,14 +11,14 @@ tags:
 - gguf-my-repo
 language:
 - en
-base_model: ZeroXClem/L3.1-Aspire-Heart-Matrix-8B
 pipeline_tag: text-generation
 library_name: transformers
 ---
-# ZeroXClem/L3.1-Aspire-Heart-Matrix-8B-Q5_0-GGUF
-This model was converted to GGUF format from [`ZeroXClem/L3.1-Aspire-Heart-Matrix-8B`](https://huggingface.co/ZeroXClem/L3.1-Aspire-Heart-Matrix-8B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
-Refer to the [original model card](https://huggingface.co/ZeroXClem/L3.1-Aspire-Heart-Matrix-8B) for more details on the model.
 ## Use with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)
@@ -31,12 +31,12 @@ Invoke the llama.cpp server or the CLI.
 ### CLI:
 ```bash
-llama-cli --hf-repo ZeroXClem/L3.1-Aspire-Heart-Matrix-8B-Q5_0-GGUF --hf-file l3.1-aspire-heart-matrix-8b-q5_0.gguf -p "The meaning to life and the universe is"
 ```
 ### Server:
 ```bash
-llama-server --hf-repo ZeroXClem/L3.1-Aspire-Heart-Matrix-8B-Q5_0-GGUF --hf-file l3.1-aspire-heart-matrix-8b-q5_0.gguf -c 2048
 ```
 Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
@@ -53,9 +53,9 @@ cd llama.cpp && LLAMA_CURL=1 make
 Step 3: Run inference through the main binary.
 ```
-./llama-cli --hf-repo ZeroXClem/L3.1-Aspire-Heart-Matrix-8B-Q5_0-GGUF --hf-file l3.1-aspire-heart-matrix-8b-q5_0.gguf -p "The meaning to life and the universe is"
 ```
 or
 ```
-./llama-server --hf-repo ZeroXClem/L3.1-Aspire-Heart-Matrix-8B-Q5_0-GGUF --hf-file l3.1-aspire-heart-matrix-8b-q5_0.gguf -c 2048
 ```

 - gguf-my-repo
 language:
 - en
+base_model: ZeroXClem/L3-Aspire-Heart-Matrix-8B
 pipeline_tag: text-generation
 library_name: transformers
 ---
+# ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF
+This model was converted to GGUF format from [`ZeroXClem/L3-Aspire-Heart-Matrix-8B`](https://huggingface.co/ZeroXClem/L3-Aspire-Heart-Matrix-8B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
+Refer to the [original model card](https://huggingface.co/ZeroXClem/L3-Aspire-Heart-Matrix-8B) for more details on the model.
 ## Use with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)
 ### CLI:
 ```bash
+llama-cli --hf-repo ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF --hf-file l3-aspire-heart-matrix-8b-q5_0.gguf -p "The meaning to life and the universe is"
 ```
 ### Server:
 ```bash
+llama-server --hf-repo ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF --hf-file l3-aspire-heart-matrix-8b-q5_0.gguf -c 2048
 ```
 Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
 Step 3: Run inference through the main binary.
 ```
+./llama-cli --hf-repo ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF --hf-file l3-aspire-heart-matrix-8b-q5_0.gguf -p "The meaning to life and the universe is"
 ```
 or
 ```
+./llama-server --hf-repo ZeroXClem/L3-Aspire-Heart-Matrix-8B-Q5_0-GGUF --hf-file l3-aspire-heart-matrix-8b-q5_0.gguf -c 2048
 ```