Instructions to use DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF with Transformers:

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

pipe = pipeline("text-generation", model="DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use DevQuasar/llama3_8b_chat_brainstorm-v2.1-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 DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF:Q2_K
# Run inference directly in the terminal:
llama cli -hf DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF:Q2_K

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF:Q2_K
# Run inference directly in the terminal:
llama cli -hf DevQuasar/llama3_8b_chat_brainstorm-v2.1-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 DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF:Q2_K
# Run inference directly in the terminal:
./llama-cli -hf DevQuasar/llama3_8b_chat_brainstorm-v2.1-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 DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF:Q2_K
# Run inference directly in the terminal:
./build/bin/llama-cli -hf DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF:Q2_K

Use Docker

docker model run hf.co/DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF:Q2_K

LM Studio
Jan

vLLM

How to use DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF:Q2_K

SGLang

How to use DevQuasar/llama3_8b_chat_brainstorm-v2.1-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 "DevQuasar/llama3_8b_chat_brainstorm-v2.1-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": "DevQuasar/llama3_8b_chat_brainstorm-v2.1-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 "DevQuasar/llama3_8b_chat_brainstorm-v2.1-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": "DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Ollama
How to use DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF with Ollama:
```
ollama run hf.co/DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF:Q2_K
```

Unsloth Studio

How to use DevQuasar/llama3_8b_chat_brainstorm-v2.1-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 DevQuasar/llama3_8b_chat_brainstorm-v2.1-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 DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF to start chatting

Docker Model Runner
How to use DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF with Docker Model Runner:
```
docker model run hf.co/DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF:Q2_K
```

Lemonade

How to use DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF:Q2_K

Run and chat with the model

lemonade run user.llama3_8b_chat_brainstorm-v2.1-GGUF-Q2_K

List all available models

lemonade list

Atomic Chat

Brainstorm GGUF

Quantized GGUF model files for DevQuasar/llama3_8b_chat_brainstorm-v2.1

Brainstorm facilitates idea exploration through interaction with a Language Model (LLM). Rather than providing direct answers, the model engages in a dialogue with users, offering probing questions aimed at fostering deeper contemplation and consideration of various facets of their ideas. Model can summaryze the discussed ideas in Markdown format.

Usage

LMStudio

With https://lmstudio.ai/ use the brainstorm.preset.json preset

llama.cpp

./main -m llama3_8b_chat_brainstorm-v2.1.Q2_K.gguf -p "### HUMAN: I'd like to build an online marketplace\n ### ASSISTANT:" -n 400 -e -ins -r "### HUMAN:\n" -r "### ASSISTANT: "

I'm doing this to 'Make knowledge free for everyone', using my personal time and resources.

If you want to support my efforts please visit my ko-fi page: https://ko-fi.com/devquasar

Also feel free to visit my website https://devquasar.com/

Downloads last month: 68

GGUF

Model size

8B params

Architecture

llama

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

Dataset used to train DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF

Collections including DevQuasar/llama3_8b_chat_brainstorm-v2.1-GGUF

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Collection

Brainstorm models • 15 items • Updated Nov 25, 2024 • 2

GGUFs

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quantized models • 234 items • Updated Mar 2 • 5