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

Libraries

How to use SandLogicTechnologies/Yi-1.5-9B-Chat-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="SandLogicTechnologies/Yi-1.5-9B-Chat-GGUF",
	filename="Yi-1.5-9B-Chat_Q4_k_m.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 SandLogicTechnologies/Yi-1.5-9B-Chat-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf SandLogicTechnologies/Yi-1.5-9B-Chat-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf SandLogicTechnologies/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-server -hf SandLogicTechnologies/Yi-1.5-9B-Chat-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf SandLogicTechnologies/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 SandLogicTechnologies/Yi-1.5-9B-Chat-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf SandLogicTechnologies/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 SandLogicTechnologies/Yi-1.5-9B-Chat-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf SandLogicTechnologies/Yi-1.5-9B-Chat-GGUF:Q4_K_M

Use Docker

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

LM Studio
Jan

vLLM

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

Use Docker

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

Ollama
How to use SandLogicTechnologies/Yi-1.5-9B-Chat-GGUF with Ollama:
```
ollama run hf.co/SandLogicTechnologies/Yi-1.5-9B-Chat-GGUF:Q4_K_M
```

Unsloth Studio

How to use SandLogicTechnologies/Yi-1.5-9B-Chat-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 SandLogicTechnologies/Yi-1.5-9B-Chat-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 SandLogicTechnologies/Yi-1.5-9B-Chat-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for SandLogicTechnologies/Yi-1.5-9B-Chat-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use SandLogicTechnologies/Yi-1.5-9B-Chat-GGUF with Docker Model Runner:
```
docker model run hf.co/SandLogicTechnologies/Yi-1.5-9B-Chat-GGUF:Q4_K_M
```

Lemonade

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

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull SandLogicTechnologies/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

Yi-1.5-9B-Chat

Yi-1.5-9B-Chat is a conversational large language model developed by 01.AI as part of the Yi-1.5 model family. It is designed to deliver strong instruction-following, reasoning, and dialogue performance while maintaining efficient deployment requirements.

The model builds on the Yi-1.5 pretrained foundation and is further optimized for chat-style interaction. It supports structured responses, multi-turn conversation, and analytical tasks such as coding, mathematical reasoning, and knowledge-based explanation.

Yi-1.5 models are trained using high-quality large-scale datasets and refined through instruction tuning to improve response usefulness and conversational reliability.

Model Overview

Model Name: Yi-1.5-9B-Chat
Model Family: Yi-1.5 Series
Base Model: 01-ai/Yi-1.5-9B
Architecture: Decoder-only Transformer
Parameter Count: 9 Billion
Context Length Options: 4K, 16K, 32K (variant dependent)
Modalities: Text
Primary Languages: English, Chinese, multilingual capability
Developer: 01.AI
License: Apache 2.0

Design Objectives

Yi-1.5-9B-Chat is built to provide high-quality conversational performance with strong reasoning ability while remaining practical for deployment.

Key design priorities include:

Reliable instruction-following behavior
Strong performance in reasoning, math, and coding tasks
Stable multi-turn dialogue handling
Flexible long-context processing
Efficient inference compared to larger models

Quantization Details

Q4_K_M

Approx. ~71% size reduction (4.96 GB)
High compression for reduced memory usage
Suitable for CPU inference and limited VRAM systems
Faster generation for local deployments
Slight reduction in reasoning precision for complex tasks

Q5_K_M

Approx. ~67% size reduction (5.83 GB)
Higher numerical precision and response stability
Improved logical consistency and coherence
Better performance on reasoning-heavy prompts
Recommended when additional memory is available

Training Overview

Pretraining Foundation

Yi-1.5 models are continuously pretrained from the original Yi models using large-scale high-quality text corpora. Training data includes hundreds of billions of tokens designed to improve language understanding, reasoning, and knowledge representation.

Instruction Alignment

The chat variant is further refined using millions of diverse instruction and conversation examples to enhance:

Conversational clarity
Prompt understanding
Structured response generation
Task-oriented interaction

This process improves performance in coding, mathematics, reasoning, and instruction-following tasks compared to earlier Yi models.

Core Capabilities

Instruction-following
Executes complex prompts and structured tasks reliably.
Conversational interaction
Maintains coherent multi-turn dialogue.
Reasoning and analytical problem solving
Strong performance in logic, math, and technical explanation.
Long-context understanding
Supports extended documents and multi-step workflows.
General knowledge and comprehension
Handles diverse topics including coding and reading comprehension.

Example Usage

llama.cpp


./llama-cli 
-m SandlogicTechnologies\Yi-1.5-9B-Chat_Q4_K_M.gguf 
-p "Explain the concept of gradient descent."

Recommended Use Cases

Conversational AI assistants
Knowledge and question answering systems
Technical explanation and tutoring
Coding and analytical reasoning support
Research experimentation with instruction-tuned models
Local deployment of capable mid-size language models

Acknowledgments

These quantized models are based on the original work by 01-ai development team.

Special thanks to:

The 01-ai team for developing and releasing the Yi-1.5-9B-Chat model.
Georgi Gerganov and the entire llama.cpp open-source community for enabling efficient model quantization and inference via the GGUF format.

Contact

For any inquiries or support, please contact us at support@sandlogic.com or visit our Website.

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GGUF

Model size

9B params

Architecture

llama

Hardware compatibility

4-bit

5-bit

Model tree for SandLogicTechnologies/Yi-1.5-9B-Chat-GGUF

Base model

01-ai/Yi-1.5-9B

Quantized

(11)

this model