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
- llama.cpp
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
metadata
language:
- en
- ru
- pl
license: apache-2.0
tags:
- ateres
- ministral
- xlam
- tool-use
- function-calling
base_model: unsloth/Ministral-3-3B-Base-2512-bnb-4bit
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
Links
- Ollama: ollama.com/chrometechhype/ateres
- HuggingFace: chrometechhype/ateres