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

Libraries

How to use bartowski/Yi-Coder-9B-Chat-GGUF with Transformers:

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

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

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("bartowski/Yi-Coder-9B-Chat-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

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

Use Docker

docker model run hf.co/bartowski/Yi-Coder-9B-Chat-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use bartowski/Yi-Coder-9B-Chat-GGUF with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/bartowski/Yi-Coder-9B-Chat-GGUF:Q4_K_M

SGLang

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

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

Lemonade

How to use bartowski/Yi-Coder-9B-Chat-GGUF with Lemonade:

Pull the model

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

Run and chat with the model

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

List all available models

lemonade list

Atomic Chat

bartowski commited on Sep 5, 2024

Commit

2f28bfc

verified ·

1 Parent(s): 673634f

Update README.md

Browse files

Files changed (1) hide show

README.md +0 -4

README.md CHANGED Viewed

@@ -37,19 +37,15 @@ Fixing tokenizer
 | -------- | ---------- | --------- | ----- | ----------- |
 | [Yi-Coder-9B-Chat-f16.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-f16.gguf) | f16 | 17.66GB | false | Full F16 weights. |
 | [Yi-Coder-9B-Chat-Q8_0.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q8_0.gguf) | Q8_0 | 9.38GB | false | Extremely high quality, generally unneeded but max available quant. |
-| [Yi-Coder-9B-Chat-Q8_0.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q8_0.gguf) | Q8_0 | 9.38GB | false | Extremely high quality, generally unneeded but max available quant. |
 | [Yi-Coder-9B-Chat-Q6_K_L.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q6_K_L.gguf) | Q6_K_L | 7.37GB | false | Uses Q8_0 for embed and output weights. Very high quality, near perfect, *recommended*. |
 | [Yi-Coder-9B-Chat-Q6_K.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q6_K.gguf) | Q6_K | 7.25GB | false | Very high quality, near perfect, *recommended*. |
-| [Yi-Coder-9B-Chat-Q6_K.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q6_K.gguf) | Q6_K | 7.25GB | false | Very high quality, near perfect, *recommended*. |
 | [Yi-Coder-9B-Chat-Q5_K_L.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q5_K_L.gguf) | Q5_K_L | 6.42GB | false | Uses Q8_0 for embed and output weights. High quality, *recommended*. |
 | [Yi-Coder-9B-Chat-Q5_K_M.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q5_K_M.gguf) | Q5_K_M | 6.26GB | false | High quality, *recommended*. |
 | [Yi-Coder-9B-Chat-Q5_K_S.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q5_K_S.gguf) | Q5_K_S | 6.11GB | false | High quality, *recommended*. |
 | [Yi-Coder-9B-Chat-Q4_K_L.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q4_K_L.gguf) | Q4_K_L | 5.52GB | false | Uses Q8_0 for embed and output weights. Good quality, *recommended*. |
 | [Yi-Coder-9B-Chat-Q4_K_M.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q4_K_M.gguf) | Q4_K_M | 5.33GB | false | Good quality, default size for must use cases, *recommended*. |
-| [Yi-Coder-9B-Chat-Q4_K_M.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q4_K_M.gguf) | Q4_K_M | 5.33GB | false | Good quality, default size for must use cases, *recommended*. |
 | [Yi-Coder-9B-Chat-Q4_K_S.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q4_K_S.gguf) | Q4_K_S | 5.07GB | false | Slightly lower quality with more space savings, *recommended*. |
 | [Yi-Coder-9B-Chat-Q4_0.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q4_0.gguf) | Q4_0 | 5.05GB | false | Legacy format, generally not worth using over similarly sized formats |
-| [Yi-Coder-9B-Chat-Q4_0_4_4.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q4_0_4_4.gguf) | Q4_0_4_4 | 5.04GB | false | Optimized for ARM inference. Should work well on all ARM chips, pick this if you're unsure. |
 | [Yi-Coder-9B-Chat-Q4_0_8_8.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q4_0_8_8.gguf) | Q4_0_8_8 | 5.04GB | false | Optimized for ARM inference. Requires 'sve' support (see link below). |
 | [Yi-Coder-9B-Chat-Q4_0_4_8.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q4_0_4_8.gguf) | Q4_0_4_8 | 5.04GB | false | Optimized for ARM inference. Requires 'i8mm' support (see link below). |
 | [Yi-Coder-9B-Chat-Q4_0_4_4.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q4_0_4_4.gguf) | Q4_0_4_4 | 5.04GB | false | Optimized for ARM inference. Should work well on all ARM chips, pick this if you're unsure. |

 | -------- | ---------- | --------- | ----- | ----------- |
 | [Yi-Coder-9B-Chat-f16.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-f16.gguf) | f16 | 17.66GB | false | Full F16 weights. |
 | [Yi-Coder-9B-Chat-Q8_0.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q8_0.gguf) | Q8_0 | 9.38GB | false | Extremely high quality, generally unneeded but max available quant. |
 | [Yi-Coder-9B-Chat-Q6_K_L.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q6_K_L.gguf) | Q6_K_L | 7.37GB | false | Uses Q8_0 for embed and output weights. Very high quality, near perfect, *recommended*. |
 | [Yi-Coder-9B-Chat-Q6_K.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q6_K.gguf) | Q6_K | 7.25GB | false | Very high quality, near perfect, *recommended*. |
 | [Yi-Coder-9B-Chat-Q5_K_L.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q5_K_L.gguf) | Q5_K_L | 6.42GB | false | Uses Q8_0 for embed and output weights. High quality, *recommended*. |
 | [Yi-Coder-9B-Chat-Q5_K_M.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q5_K_M.gguf) | Q5_K_M | 6.26GB | false | High quality, *recommended*. |
 | [Yi-Coder-9B-Chat-Q5_K_S.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q5_K_S.gguf) | Q5_K_S | 6.11GB | false | High quality, *recommended*. |
 | [Yi-Coder-9B-Chat-Q4_K_L.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q4_K_L.gguf) | Q4_K_L | 5.52GB | false | Uses Q8_0 for embed and output weights. Good quality, *recommended*. |
 | [Yi-Coder-9B-Chat-Q4_K_M.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q4_K_M.gguf) | Q4_K_M | 5.33GB | false | Good quality, default size for must use cases, *recommended*. |
 | [Yi-Coder-9B-Chat-Q4_K_S.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q4_K_S.gguf) | Q4_K_S | 5.07GB | false | Slightly lower quality with more space savings, *recommended*. |
 | [Yi-Coder-9B-Chat-Q4_0.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q4_0.gguf) | Q4_0 | 5.05GB | false | Legacy format, generally not worth using over similarly sized formats |
 | [Yi-Coder-9B-Chat-Q4_0_8_8.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q4_0_8_8.gguf) | Q4_0_8_8 | 5.04GB | false | Optimized for ARM inference. Requires 'sve' support (see link below). |
 | [Yi-Coder-9B-Chat-Q4_0_4_8.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q4_0_4_8.gguf) | Q4_0_4_8 | 5.04GB | false | Optimized for ARM inference. Requires 'i8mm' support (see link below). |
 | [Yi-Coder-9B-Chat-Q4_0_4_4.gguf](https://huggingface.co/bartowski/Yi-Coder-9B-Chat-GGUF/blob/main/Yi-Coder-9B-Chat-Q4_0_4_4.gguf) | Q4_0_4_4 | 5.04GB | false | Optimized for ARM inference. Should work well on all ARM chips, pick this if you're unsure. |