Instructions to use Sunbird/Sunflower-14B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Sunbird/Sunflower-14B-GGUF with Transformers:

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

pipe = pipeline("text-generation", model="Sunbird/Sunflower-14B-GGUF")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Sunbird/Sunflower-14B-GGUF", dtype="auto")

llama-cpp-python

How to use Sunbird/Sunflower-14B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Sunbird/Sunflower-14B-GGUF",
	filename="sunflower-14B-f16.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Sunbird/Sunflower-14B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Sunbird/Sunflower-14B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf Sunbird/Sunflower-14B-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 Sunbird/Sunflower-14B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf Sunbird/Sunflower-14B-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 Sunbird/Sunflower-14B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Sunbird/Sunflower-14B-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 Sunbird/Sunflower-14B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Sunbird/Sunflower-14B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/Sunbird/Sunflower-14B-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use Sunbird/Sunflower-14B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Sunbird/Sunflower-14B-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": "Sunbird/Sunflower-14B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Sunbird/Sunflower-14B-GGUF:Q4_K_M

SGLang

How to use Sunbird/Sunflower-14B-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 "Sunbird/Sunflower-14B-GGUF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Sunbird/Sunflower-14B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "Sunbird/Sunflower-14B-GGUF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Sunbird/Sunflower-14B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use Sunbird/Sunflower-14B-GGUF with Ollama:
```
ollama run hf.co/Sunbird/Sunflower-14B-GGUF:Q4_K_M
```

Unsloth Studio

How to use Sunbird/Sunflower-14B-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 Sunbird/Sunflower-14B-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 Sunbird/Sunflower-14B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Sunbird/Sunflower-14B-GGUF to start chatting

How to use Sunbird/Sunflower-14B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf Sunbird/Sunflower-14B-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "Sunbird/Sunflower-14B-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use Sunbird/Sunflower-14B-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf Sunbird/Sunflower-14B-GGUF:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default Sunbird/Sunflower-14B-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat new
Docker Model Runner
How to use Sunbird/Sunflower-14B-GGUF with Docker Model Runner:
```
docker model run hf.co/Sunbird/Sunflower-14B-GGUF:Q4_K_M
```

Lemonade

How to use Sunbird/Sunflower-14B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Sunbird/Sunflower-14B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Sunflower-14B-GGUF-Q4_K_M

List all available models

lemonade list

@@ -43,3 +43,11 @@ sunflower-q8_0.gguf filter=lfs diff=lfs merge=lfs -text
 sunflower-iq1_s.gguf filter=lfs diff=lfs merge=lfs -text
 sunflower-iq2_xxs.gguf filter=lfs diff=lfs merge=lfs -text
 sunflower-tq1_0.gguf filter=lfs diff=lfs merge=lfs -text

 sunflower-iq1_s.gguf filter=lfs diff=lfs merge=lfs -text
 sunflower-iq2_xxs.gguf filter=lfs diff=lfs merge=lfs -text
 sunflower-tq1_0.gguf filter=lfs diff=lfs merge=lfs -text
+sunflower-14B-f16.gguf filter=lfs diff=lfs merge=lfs -text
+sunflower-14B-iq1_s.gguf filter=lfs diff=lfs merge=lfs -text
+sunflower-14B-iq2_xxs.gguf filter=lfs diff=lfs merge=lfs -text
+sunflower-14B-q4_k_m.gguf filter=lfs diff=lfs merge=lfs -text
+sunflower-14B-q5_k_m.gguf filter=lfs diff=lfs merge=lfs -text
+sunflower-14B-q6_k.gguf filter=lfs diff=lfs merge=lfs -text
+sunflower-14B-q8_0.gguf filter=lfs diff=lfs merge=lfs -text
+sunflower-14B-tq1_0.gguf filter=lfs diff=lfs merge=lfs -text

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9717ce1e0643a19b3686e86162ce04db8bd01635954eb85284826a3834ebc0f8
 size 7743552

Sunbird
/

Sunflower-14B-GGUF

Add GGUF quantized models

+version https://git-lfs.github.com/spec/v1
+oid sha256:8a73f17db7a64177b191fd4b3a33753016deed5b089e953899ee09bf08267264
+size 29543424576

+version https://git-lfs.github.com/spec/v1
+oid sha256:3531fc18eb0ad4ee323569fc948bd433c21be300b6482c553b6b3dd52a33b3bc
+size 3579935520

+version https://git-lfs.github.com/spec/v1
+oid sha256:c5fde2bc7158e72d95b6df46f79917bc3438786a8e03a694d89b007417be6aa1
+size 4299193120

+version https://git-lfs.github.com/spec/v1
+oid sha256:686a296cd0db9f71304bfc2bf2358ec66469e02ffcb02368328692d90b02db6e
+size 9001754400

+version https://git-lfs.github.com/spec/v1
+oid sha256:8f2b006af3002f5744f06eec68b8cfea87e23b8a4d55ac0a595d50685d5cdf2e
+size 10514571040

+version https://git-lfs.github.com/spec/v1
+oid sha256:a0920d39e6749e43a50b2bc8924980a616b4ef91017552bae0740666eea9c765
+size 12121938720

+version https://git-lfs.github.com/spec/v1
+oid sha256:b090e82acf38e2e299bc9eaa56d4cad6ee5f4eb62c7267182a4099b9ed57a594
+size 15698535200

+version https://git-lfs.github.com/spec/v1
+oid sha256:0d97950ace975d122e4edb1200ce98ad63df25118d20505497ee296c8f4160cf
+size 3870285600

	@@ -0,0 +1,3 @@

	@@ -0,0 +1,3 @@

	@@ -0,0 +1,3 @@

	@@ -0,0 +1,3 @@