Instructions to use QuantFactory/AI-Sweden-Llama-3-8B-Instruct-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 QuantFactory/AI-Sweden-Llama-3-8B-Instruct-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 QuantFactory/AI-Sweden-Llama-3-8B-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf QuantFactory/AI-Sweden-Llama-3-8B-Instruct-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 QuantFactory/AI-Sweden-Llama-3-8B-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf QuantFactory/AI-Sweden-Llama-3-8B-Instruct-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 QuantFactory/AI-Sweden-Llama-3-8B-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf QuantFactory/AI-Sweden-Llama-3-8B-Instruct-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 QuantFactory/AI-Sweden-Llama-3-8B-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf QuantFactory/AI-Sweden-Llama-3-8B-Instruct-GGUF:Q4_K_M

Use Docker

docker model run hf.co/QuantFactory/AI-Sweden-Llama-3-8B-Instruct-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use QuantFactory/AI-Sweden-Llama-3-8B-Instruct-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "QuantFactory/AI-Sweden-Llama-3-8B-Instruct-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": "QuantFactory/AI-Sweden-Llama-3-8B-Instruct-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/QuantFactory/AI-Sweden-Llama-3-8B-Instruct-GGUF:Q4_K_M

Ollama
How to use QuantFactory/AI-Sweden-Llama-3-8B-Instruct-GGUF with Ollama:
```
ollama run hf.co/QuantFactory/AI-Sweden-Llama-3-8B-Instruct-GGUF:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use QuantFactory/AI-Sweden-Llama-3-8B-Instruct-GGUF with Docker Model Runner:
```
docker model run hf.co/QuantFactory/AI-Sweden-Llama-3-8B-Instruct-GGUF:Q4_K_M
```

Lemonade

How to use QuantFactory/AI-Sweden-Llama-3-8B-Instruct-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull QuantFactory/AI-Sweden-Llama-3-8B-Instruct-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.AI-Sweden-Llama-3-8B-Instruct-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

AI-Sweden-Llama-3-8B-Instruct-GGUF / README.md

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metadata

license: apache-2.0
datasets: teknium/OpenHermes-2.5
base_model: AI-Sweden-Models/Llama-3-8B-instruct
pipeline_tag: text-generation

QuantFactory/AI-Sweden-Llama-3-8B-Instruct-GGUF

This is quantized version of AI-Sweden-Models/Llama-3-8B-instruct created suing llama.cpp

Model Description

Checkpoint 1

Training setup

The training was perfomed on the LUMI supercomputer within the DeployAI EU project. Based of the base model AI-Sweden-Models/Llama-3-8B.

Dataset

A data recipe by: 42 Labs

How to use

import transformers
import torch

model_id = "AI-Sweden-Models/Llama-3-8B-instruct"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

messages = [
    {"role": "system", "content": "Du är en hjälpsam assistant som svarar klokt och vänligt."},
    {"role": "user", "content": "Hur gör man pannkakor? Och vad behöver man handla? Undrar också vad 5+6 är.."},
]

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<|eot_id|>")
]

outputs = pipeline(
    messages,
    max_new_tokens=256,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.6,
    top_p=0.9,
)
print(outputs[0]["generated_text"][-1])

>>> "För att göra pannkakor behöver du följande ingredienser:
- 1 kopp vetemjöl
- 1 tesked bakpulver
- 1/4 tesked salt
- 1 kopp mjölk
- 1 stort ägg
- 2 matskedar smält smör eller olja

För att börja, blanda vetemjölet, bakpulvret och saltet i en bunke. I en annan skål, vispa ihop mjölken, ägget och smöret eller oljan. 
Tillsätt de våta ingredienserna till de torra ingredienserna och blanda tills det är väl blandat. 
Låt smeten vila i cirka 10 minuter.

För att göra pannkakorna, värm en non-stick-panna eller stekpanna över medelvärme. 
När den är varm, häll smeten på pannan och grädda tills kanterna börjar torka ut och toppen är fast. 
Vänd pannkakan med en stekspade och grädda den andra sidan tills den är gyllenbrun. 
Upprepa med resten av smeten.

När det gäller 5+6 är svaret 11."