Instructions to use tensorblock/Sailor-7B-Chat-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use tensorblock/Sailor-7B-Chat-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="tensorblock/Sailor-7B-Chat-GGUF",
	filename="Sailor-7B-Chat-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 tensorblock/Sailor-7B-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 tensorblock/Sailor-7B-Chat-GGUF:Q2_K
# Run inference directly in the terminal:
llama-cli -hf tensorblock/Sailor-7B-Chat-GGUF:Q2_K

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf tensorblock/Sailor-7B-Chat-GGUF:Q2_K
# Run inference directly in the terminal:
llama-cli -hf tensorblock/Sailor-7B-Chat-GGUF:Q2_K

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 tensorblock/Sailor-7B-Chat-GGUF:Q2_K
# Run inference directly in the terminal:
./llama-cli -hf tensorblock/Sailor-7B-Chat-GGUF:Q2_K

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 tensorblock/Sailor-7B-Chat-GGUF:Q2_K
# Run inference directly in the terminal:
./build/bin/llama-cli -hf tensorblock/Sailor-7B-Chat-GGUF:Q2_K

Use Docker

docker model run hf.co/tensorblock/Sailor-7B-Chat-GGUF:Q2_K

LM Studio
Jan
Ollama
How to use tensorblock/Sailor-7B-Chat-GGUF with Ollama:
```
ollama run hf.co/tensorblock/Sailor-7B-Chat-GGUF:Q2_K
```

Unsloth Studio

How to use tensorblock/Sailor-7B-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 tensorblock/Sailor-7B-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 tensorblock/Sailor-7B-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 tensorblock/Sailor-7B-Chat-GGUF to start chatting

Docker Model Runner
How to use tensorblock/Sailor-7B-Chat-GGUF with Docker Model Runner:
```
docker model run hf.co/tensorblock/Sailor-7B-Chat-GGUF:Q2_K
```

Lemonade

How to use tensorblock/Sailor-7B-Chat-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull tensorblock/Sailor-7B-Chat-GGUF:Q2_K

Run and chat with the model

lemonade run user.Sailor-7B-Chat-GGUF-Q2_K

List all available models

lemonade list

morriszms commited on Jan 27

Commit

57729e4

verified ·

1 Parent(s): 621d8f3

Keep Q2_K/Q3_K_M gguf only

Browse files

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:34f0f58d1e13e4cd39ec42701c10246055b7b5da9ab08fe588f09cfeba46dcd6
-size 4217967456

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:08740c5dcca93986ca6e6cae57361175f4d80798811a188551c71eab34c12bdf
-size 3569161056

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:55556c660a012e2c64b820df3585d8baaa6979529f8d53b71951aecde1e7aa43
-size 4511908704

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:d469fb4324e924182371d29e0f7c7a6116ebb691dc71a9155340a8775d44eed1
-size 4767105888

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:6e275ed56680927357652695827806581192dc370af001cd0df6f8fe08b9c26d
-size 4542841696