Instructions to use SafeAgent/safeagent-7b-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SafeAgent/safeagent-7b-v1 with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="SafeAgent/safeagent-7b-v1",
	filename="safeagent-7b-v1.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use SafeAgent/safeagent-7b-v1 with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf SafeAgent/safeagent-7b-v1
# Run inference directly in the terminal:
llama-cli -hf SafeAgent/safeagent-7b-v1

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf SafeAgent/safeagent-7b-v1
# Run inference directly in the terminal:
llama-cli -hf SafeAgent/safeagent-7b-v1

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 SafeAgent/safeagent-7b-v1
# Run inference directly in the terminal:
./llama-cli -hf SafeAgent/safeagent-7b-v1

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 SafeAgent/safeagent-7b-v1
# Run inference directly in the terminal:
./build/bin/llama-cli -hf SafeAgent/safeagent-7b-v1

Use Docker

docker model run hf.co/SafeAgent/safeagent-7b-v1

LM Studio
Jan
Ollama
How to use SafeAgent/safeagent-7b-v1 with Ollama:
```
ollama run hf.co/SafeAgent/safeagent-7b-v1
```

Unsloth Studio new

How to use SafeAgent/safeagent-7b-v1 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 SafeAgent/safeagent-7b-v1 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 SafeAgent/safeagent-7b-v1 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for SafeAgent/safeagent-7b-v1 to start chatting

Docker Model Runner
How to use SafeAgent/safeagent-7b-v1 with Docker Model Runner:
```
docker model run hf.co/SafeAgent/safeagent-7b-v1
```

Lemonade

How to use SafeAgent/safeagent-7b-v1 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull SafeAgent/safeagent-7b-v1

Run and chat with the model

lemonade run user.safeagent-7b-v1-{{QUANT_TAG}}

List all available models

lemonade list

Gomzjaz commited on 26 days ago

Commit

8d58d60

verified ·

1 Parent(s): 4d9d038

Update README.md

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README.md +67 -68

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@@ -1,68 +1,67 @@
----
-language:
-- en
-license: apache-2.0
-tags:
-- safeagent
-- mistral
-- instruction-tuning
-- local-ai
-- self-hosted
----
-# SafeAgent 7B v1
-**The AI model powering [SafeAgent](https://safeagent.dev) ? your personal AI agent that runs entirely on your machine.**
-SafeAgent lets you chat with AI, read your emails, search the web, manage GitHub, post to Slack, and automate workflows ? all running locally. Your data never leaves your network. No subscriptions. No cloud dependency.
-## Run It Now
-```bash
-ollama run SafeAgent/safeagent-7b-v1
-```
-## What SafeAgent Can Do With This Model
-- Read and send emails (Gmail, Outlook, Yahoo)
-- Search the web and summarise results
-- Write, fix, and explain code
-- Plan trips, book restaurants, compare products
-- Automate workflows and scheduled tasks
-- Everything stays on your machine -- AES-256 encrypted
-## Install SafeAgent
-```bash
-curl -sL https://www.safeagent.dev/docker-compose.yml -o docker-compose.yml && docker compose up
-```
-Open http://localhost:3000 -- running in 30 seconds.
-## Model Details
-| Property | Value |
-|----------|-------|
-| Base model | Mistral 7B v0.1 |
-| Fine-tuning method | QLoRA 4-bit |
-| Training data | 80,000 OpenOrca instruction examples |
-| Training hardware | NVIDIA RTX 5080 16GB |
-| Training time | 20 hours |
-| Final loss | 0.5564 |
-| Format | GGUF f16 |
-## Why Local AI?
-| Cloud AI | SafeAgent |
-|----------|-----------|
-| Your data on their servers | Everything on your machine |
-| $20-100/month | Free forever |
-| Rate limited | No limits -- your hardware |
-| Vendor lock-in | Open source, always |
-| They train on your data | Your data stays yours |
-## Links
-- Website: https://safeagent.dev
-- DockerHub: https://hub.docker.com/u/gurmukhs
-- Built by Gurmukh Singh: https://www.linkedin.com/in/gurmukh-singh-38a1a4246/

+---
+language:
+- en
+license: apache-2.0
+tags:
+- safeagent
+- mistral
+- instruction-tuning
+- local-ai
+- self-hosted
+---
+# SafeAgent 7B v1
+**The AI model powering [SafeAgent](https://safeagent.dev) ? your personal AI agent that runs entirely on your machine.**
+SafeAgent lets you chat with AI, read your emails, search the web, manage GitHub, post to Slack, and automate workflows ? all running locally. Your data never leaves your network. No subscriptions. No cloud dependency.
+## Run It Now
+```bash
+ollama run SafeAgent/safeagent-7b-v1
+```
+## What SafeAgent Can Do With This Model
+- Read and send emails (Gmail, Outlook, Yahoo)
+- Search the web and summarise results
+- Write, fix, and explain code
+- Plan trips, book restaurants, compare products
+- Automate workflows and scheduled tasks
+- Everything stays on your machine -- AES-256 encrypted
+## Install SafeAgent
+```bash
+curl -sL https://www.safeagent.dev/docker-compose.yml -o docker-compose.yml && docker compose up
+```
+Open http://localhost:3000 -- running in 30 seconds.
+## Model Details
+| Property | Value |
+|----------|-------|
+| Base model | Mistral 7B v0.1 |
+| Fine-tuning method | QLoRA 4-bit |
+| Training data | 80,000 OpenOrca instruction examples |
+| Training time | 20 hours |
+| Final loss | 0.5564 |
+| Format | GGUF f16 |
+## Why Local AI?
+| Cloud AI | SafeAgent |
+|----------|-----------|
+| Your data on their servers | Everything on your machine |
+| $20-100/month | Free forever |
+| Rate limited | No limits -- your hardware |
+| Vendor lock-in | Open source, always |
+| They train on your data | Your data stays yours |
+## Links
+- Website: https://safeagent.dev
+- DockerHub: https://hub.docker.com/u/gurmukhs
+- Built by Gurmukh Singh: https://www.linkedin.com/in/gurmukh-singh-38a1a4246/