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

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use afrideva/llama3_8b_chat_brainstorm-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 afrideva/llama3_8b_chat_brainstorm-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf afrideva/llama3_8b_chat_brainstorm-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf afrideva/llama3_8b_chat_brainstorm-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf afrideva/llama3_8b_chat_brainstorm-GGUF:Q4_K_M

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 afrideva/llama3_8b_chat_brainstorm-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf afrideva/llama3_8b_chat_brainstorm-GGUF:Q4_K_M

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 afrideva/llama3_8b_chat_brainstorm-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf afrideva/llama3_8b_chat_brainstorm-GGUF:Q4_K_M

Use Docker

docker model run hf.co/afrideva/llama3_8b_chat_brainstorm-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use afrideva/llama3_8b_chat_brainstorm-GGUF with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/afrideva/llama3_8b_chat_brainstorm-GGUF:Q4_K_M

Ollama
How to use afrideva/llama3_8b_chat_brainstorm-GGUF with Ollama:
```
ollama run hf.co/afrideva/llama3_8b_chat_brainstorm-GGUF:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use afrideva/llama3_8b_chat_brainstorm-GGUF with Docker Model Runner:
```
docker model run hf.co/afrideva/llama3_8b_chat_brainstorm-GGUF:Q4_K_M
```

Lemonade

How to use afrideva/llama3_8b_chat_brainstorm-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull afrideva/llama3_8b_chat_brainstorm-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.llama3_8b_chat_brainstorm-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

llama3_8b_chat_brainstorm-GGUF

Quantized GGUF model files for llama3_8b_chat_brainstorm from DevQuasar

Original Model Card:

Model intention

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.

Examples

Inference code

https://github.com/csabakecskemeti/ai_utils/blob/main/brainstorm_inference.py

Example generations

[USER] (Ctrl+C to exit): Today I'm gonna buy all healthy product at the grocery store.

[CHAT]: What kind of healthy products are you thinking of buying?

[USER] (Ctrl+C to exit): Mainly vegetables, and some lean white meet like fish and chicken

[CHAT]: Have you considered organic produce for your veggies?

[USER] (Ctrl+C to exit): I'm thinking to invest in a franchise to get a new source of income.

[CHAT]: That's an interesting idea! What kind of franchises are you considering?

[USER] (Ctrl+C to exit): Something that is a small upfront cost, not sure what would be a great choice.

[CHAT]: Have you considered food-related franchises like pizza or ice cream shops? They often have low startup costs.

[USER] (Ctrl+C to exit): But that risky due to publich healt requirements

[CHAT]: You're right, there are some regulations to consider. How would you plan to mitigate those risks?

[USER] (Ctrl+C to exit): I guess do some other non food related franchise

[CHAT]: What about a business service franchise like janitorial or landscaping services? Those might have lower regulatory burdens.

Downloads last month: 40

GGUF

Model size

8B params

Architecture

llama

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

View +1 variant

Model tree for afrideva/llama3_8b_chat_brainstorm-GGUF

Base model

meta-llama/Meta-Llama-3-8B

Finetuned

DevQuasar/llama3_8b_chat_brainstorm

Quantized

(1)

this model

afrideva
/

llama3_8b_chat_brainstorm-GGUF