Instructions to use seyf1elislam/dolphin-2.9-llama3-8b-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use seyf1elislam/dolphin-2.9-llama3-8b-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="seyf1elislam/dolphin-2.9-llama3-8b-GGUF",
	filename="dolphin-2.9-llama3-8b.Q2_K.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use seyf1elislam/dolphin-2.9-llama3-8b-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf seyf1elislam/dolphin-2.9-llama3-8b-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf seyf1elislam/dolphin-2.9-llama3-8b-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf seyf1elislam/dolphin-2.9-llama3-8b-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf seyf1elislam/dolphin-2.9-llama3-8b-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 seyf1elislam/dolphin-2.9-llama3-8b-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf seyf1elislam/dolphin-2.9-llama3-8b-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 seyf1elislam/dolphin-2.9-llama3-8b-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf seyf1elislam/dolphin-2.9-llama3-8b-GGUF:Q4_K_M

Use Docker

docker model run hf.co/seyf1elislam/dolphin-2.9-llama3-8b-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use seyf1elislam/dolphin-2.9-llama3-8b-GGUF with Ollama:
```
ollama run hf.co/seyf1elislam/dolphin-2.9-llama3-8b-GGUF:Q4_K_M
```

Unsloth Studio

How to use seyf1elislam/dolphin-2.9-llama3-8b-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 seyf1elislam/dolphin-2.9-llama3-8b-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 seyf1elislam/dolphin-2.9-llama3-8b-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for seyf1elislam/dolphin-2.9-llama3-8b-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use seyf1elislam/dolphin-2.9-llama3-8b-GGUF with Docker Model Runner:
```
docker model run hf.co/seyf1elislam/dolphin-2.9-llama3-8b-GGUF:Q4_K_M
```

Lemonade

How to use seyf1elislam/dolphin-2.9-llama3-8b-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull seyf1elislam/dolphin-2.9-llama3-8b-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.dolphin-2.9-llama3-8b-GGUF-Q4_K_M

List all available models

lemonade list

dolphin-2.9-llama3-8b

Model creator: cognitivecomputations
Original model: dolphin-2.9-llama3-8b

Description

This repo contains GGUF format model files for cognitivecomputations's dolphin-2.9-llama3-8b .

Provided files

Name	Quant method	Bits	Size	Max RAM required	Use case
dolphin-2.9-llama3-8b.Q2_K.gguf	Q2_K	2	2.72 GB	5.22 GB	significant quality loss - not recommended for most purposes
dolphin-2.9-llama3-8b.Q3_K_M.gguf	Q3_K_M	3	3.52 GB	6.02 GB	very small, high quality loss
dolphin-2.9-llama3-8b.Q4_K_S.gguf	Q4_K_S	4	4.14 GB	6.64 GB	small, greater quality loss
dolphin-2.9-llama3-8b.Q4_K_M.gguf	Q4_K_M	4	4.37 GB	6.87 GB	medium, balanced quality - recommended
dolphin-2.9-llama3-8b.Q5_K_M.gguf	Q5_K_M	5	5.13 GB	7.63 GB	large, very low quality loss - recommended
dolphin-2.9-llama3-8b.Q6_K.gguf	Q6_K	6	5.94 GB	8.44 GB	very large, extremely low quality loss
dolphin-2.9-llama3-8b.Q8_0.gguf	Q8_0	8	7.70 GB	10.20 GB	very large, extremely low quality loss - not recommended

Downloads last month: 90

GGUF

Model size

8B params

Architecture

llama

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

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Model tree for seyf1elislam/dolphin-2.9-llama3-8b-GGUF

Base model

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

Finetuned

dphn/dolphin-2.9-llama3-8b

Quantized

(22)

this model