Instructions to use gaianet/Yi-1.5-9B-Chat-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use gaianet/Yi-1.5-9B-Chat-GGUF with Transformers:

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

pipe = pipeline("text-generation", model="gaianet/Yi-1.5-9B-Chat-GGUF")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("gaianet/Yi-1.5-9B-Chat-GGUF")
model = AutoModelForCausalLM.from_pretrained("gaianet/Yi-1.5-9B-Chat-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use gaianet/Yi-1.5-9B-Chat-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 gaianet/Yi-1.5-9B-Chat-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf gaianet/Yi-1.5-9B-Chat-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 gaianet/Yi-1.5-9B-Chat-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf gaianet/Yi-1.5-9B-Chat-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 gaianet/Yi-1.5-9B-Chat-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf gaianet/Yi-1.5-9B-Chat-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 gaianet/Yi-1.5-9B-Chat-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf gaianet/Yi-1.5-9B-Chat-GGUF:Q4_K_M

Use Docker

docker model run hf.co/gaianet/Yi-1.5-9B-Chat-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use gaianet/Yi-1.5-9B-Chat-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "gaianet/Yi-1.5-9B-Chat-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": "gaianet/Yi-1.5-9B-Chat-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/gaianet/Yi-1.5-9B-Chat-GGUF:Q4_K_M

SGLang

How to use gaianet/Yi-1.5-9B-Chat-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 "gaianet/Yi-1.5-9B-Chat-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": "gaianet/Yi-1.5-9B-Chat-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 "gaianet/Yi-1.5-9B-Chat-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": "gaianet/Yi-1.5-9B-Chat-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use gaianet/Yi-1.5-9B-Chat-GGUF with Ollama:
```
ollama run hf.co/gaianet/Yi-1.5-9B-Chat-GGUF:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use gaianet/Yi-1.5-9B-Chat-GGUF with Docker Model Runner:
```
docker model run hf.co/gaianet/Yi-1.5-9B-Chat-GGUF:Q4_K_M
```

Lemonade

How to use gaianet/Yi-1.5-9B-Chat-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull gaianet/Yi-1.5-9B-Chat-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Yi-1.5-9B-Chat-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

apepkuss79 commited on Jun 12, 2024

Commit

eb3a131

verified ·

1 Parent(s): 86a6064

Update README.md

Browse files

Files changed (1) hide show

README.md +0 -18

README.md CHANGED Viewed

@@ -46,22 +46,4 @@ chat_ctx_size: `4096`
 - Customize your node: https://docs.gaianet.ai/node-guide/customize
-## Quantized GGUF Models
-| Name | Quant method | Bits | Size | Use case |
-| ---- | ---- | ---- | ---- | ----- |
-| [Yi-1.5-9B-Chat-Q2_K.gguf](https://huggingface.co/gaianet/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q2_K.gguf)     | Q2_K   | 2 |3.35 GB| smallest, significant quality loss - not recommended for most purposes |
-| [Yi-1.5-9B-Chat-Q3_K_L.gguf](https://huggingface.co/gaianet/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q3_K_L.gguf) | Q3_K_L | 3 | 3.24 GB| small, substantial quality loss |
-| [Yi-1.5-9B-Chat-Q3_K_M.gguf](https://huggingface.co/gaianet/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q3_K_M.gguf) | Q3_K_M | 3 | 2.99 GB| very small, high quality loss |
-| [Yi-1.5-9B-Chat-Q3_K_S.gguf](https://huggingface.co/gaianet/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q3_K_S.gguf) | Q3_K_S | 3 | 2.71 GB| very small, high quality loss |
-| [Yi-1.5-9B-Chat-Q4_0.gguf](https://huggingface.co/gaianet/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q4_0.gguf)     | Q4_0   | 4 | 3.48 GB| legacy; small, very high quality loss - prefer using Q3_K_M |
-| [Yi-1.5-9B-Chat-Q4_K_M.gguf](https://huggingface.co/gaianet/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q4_K_M.gguf) | Q4_K_M | 4 | 3.67 GB| medium, balanced quality - recommended |
-| [Yi-1.5-9B-Chat-Q4_K_S.gguf](https://huggingface.co/gaianet/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q4_K_S.gguf) | Q4_K_S | 4 | 3.50 GB| small, greater quality loss |
-| [Yi-1.5-9B-Chat-Q5_0.gguf](https://huggingface.co/gaianet/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q5_0.gguf)     | Q5_0   | 5 | 4.20 GB| legacy; medium, balanced quality - prefer using Q4_K_M |
-| [Yi-1.5-9B-Chat-Q5_K_M.gguf](https://huggingface.co/gaianet/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q5_K_M.gguf) | Q5_K_M | 5 | 4.30 GB| large, very low quality loss - recommended |
-| [Yi-1.5-9B-Chat-Q5_K_S.gguf](https://huggingface.co/gaianet/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q5_K_S.gguf) | Q5_K_S | 5 | 4.20 GB| large, low quality loss - recommended |
-| [Yi-1.5-9B-Chat-Q6_K.gguf](https://huggingface.co/gaianet/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q6_K.gguf)     | Q6_K   | 6 | 4.97 GB| very large, extremely low quality loss |
-| [Yi-1.5-9B-Chat-Q8_0.gguf](https://huggingface.co/gaianet/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q8_0.gguf)     | Q8_0   | 8 | 6.44 GB| very large, extremely low quality loss - not recommended |
-| [Yi-1.5-9B-Chat-f16.gguf](https://huggingface.co/gaianet/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-f16.gguf)     | f16   | 16 | 17.7 GB| |
 *Quantized with llama.cpp b3135*


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47	- Customize your node: https://docs.gaianet.ai/node-guide/customize
48


















49	Quantized with llama.cpp b3135