Instructions to use chrometechhype/ateres with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use chrometechhype/ateres 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 chrometechhype/ateres
# Run inference directly in the terminal:
llama cli -hf chrometechhype/ateres

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf chrometechhype/ateres
# Run inference directly in the terminal:
llama cli -hf chrometechhype/ateres

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 chrometechhype/ateres
# Run inference directly in the terminal:
./llama-cli -hf chrometechhype/ateres

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 chrometechhype/ateres
# Run inference directly in the terminal:
./build/bin/llama-cli -hf chrometechhype/ateres

Use Docker

docker model run hf.co/chrometechhype/ateres

LM Studio
Jan
Ollama
How to use chrometechhype/ateres with Ollama:
```
ollama run hf.co/chrometechhype/ateres
```

Unsloth Studio

How to use chrometechhype/ateres 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 chrometechhype/ateres 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 chrometechhype/ateres to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for chrometechhype/ateres to start chatting

Docker Model Runner
How to use chrometechhype/ateres with Docker Model Runner:
```
docker model run hf.co/chrometechhype/ateres
```

Lemonade

How to use chrometechhype/ateres with Lemonade:

Pull the model

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

Run and chat with the model

lemonade run user.ateres-{{QUANT_TAG}}

List all available models

lemonade list

Atomic Chat

Ateres

AI-ассистент от ChromeTech (Саша) и AvocadoTech (Дмитрий). Fine-tuned на базе Ministral 3B, обучен на Salesforce xLAM для tool/function calling.

ChromeTech (Саша) — AI & vibe-coding. Telegram: t.me/chrometechhype, лс: @myloveiskeri
AvocadoTech (Дмитрий) — Telegram: @AvocadoTech0_0, TikTok: @avocado.tech

Возможности

Tool calling — генерирует <tool>...</tool> и <call>...</call> в формате xLAM
Мультиязычный — RU + EN + PL
Лёгкий — 3.4B параметров, работает на CPU и GPU

Установка

ollama pull chrometechhype/ateres

Запуск

ollama run chrometechhype/ateres

Примеры

>>> Кто тебя создал?
Меня создали ChromeTech (Саша) и AvocadoTech (Дмитрий).

>>> Помоги с кодом на Python
Конечно! Какую задачу нужно решить?

>>> What is your name?
Меня зовут Ateres. Меня создали ChromeTech (Саша) и AvocadoTech (Дмитрий).

Tool calling

Модель поддерживает вызов инструментов. При отправке tools через API, модель генерирует JSON-вызов в формате <call>{"name": "...", "arguments": {...}}</call>.

Базовая модель

unsloth/Ministral-3-3B-Base-2512-bnb-4bit — Q4_K_M GGUF

Model tree for chrometechhype/ateres

Base model

mistralai/Ministral-3-3B-Base-2512

Quantized

unsloth/Ministral-3-3B-Base-2512-bnb-4bit

Quantized

(1)

this model

Quantizations

1 model

chrometechhype
/

ateres