Skip to main content

Utils for Unsloth

Project description

unsloth logo

Unsloth Zoo - Utils for Unsloth!

✨ Finetune for Free

All notebooks are beginner friendly! Add your dataset, click "Run All", and you'll get a 2x faster finetuned model which can be exported to GGUF, Ollama, vLLM or uploaded to Hugging Face.

Unsloth supports Free Notebooks Performance Memory use
Llama 3.2 (3B) ▶️ Start for free 2x faster 60% less
Llama 3.1 (8B) ▶️ Start for free 2x faster 60% less
Phi-3.5 (mini) ▶️ Start for free 2x faster 50% less
Gemma 2 (9B) ▶️ Start for free 2x faster 63% less
Mistral Small (22B) ▶️ Start for free 2x faster 60% less
Ollama ▶️ Start for free 1.9x faster 43% less
Mistral v0.3 (7B) ▶️ Start for free 2.2x faster 73% less
ORPO ▶️ Start for free 1.9x faster 43% less
DPO Zephyr ▶️ Start for free 1.9x faster 43% less

🔗 Links and Resources

Type Links
📚 Documentation & Wiki Read Our Docs
  Twitter (aka X) Follow us on X
💾 Installation unsloth/README.md
🥇 Benchmarking Performance Tables
🌐 Released Models Unsloth Releases
✍️ Blog Read our Blogs

⭐ Key Features

  • All kernels written in OpenAI's Triton language. Manual backprop engine.
  • 0% loss in accuracy - no approximation methods - all exact.
  • No change of hardware. Supports NVIDIA GPUs since 2018+. Minimum CUDA Capability 7.0 (V100, T4, Titan V, RTX 20, 30, 40x, A100, H100, L40 etc) Check your GPU! GTX 1070, 1080 works, but is slow.
  • Works on Linux and Windows via WSL.
  • Supports 4bit and 16bit QLoRA / LoRA finetuning via bitsandbytes.
  • Open source trains 5x faster - see Unsloth Pro for up to 30x faster training!
  • If you trained a model with 🦥Unsloth, you can use this cool sticker!  

💾 Installation Instructions

These are utilities for Unsloth, so install Unsloth as well! For stable releases for Unsloth Zoo, use pip install unsloth_zoo. We recommend pip install "unsloth_zoo @ git+https://github.com/unslothai/unsloth-zoo.git" for most installations though.

pip install unsloth_zoo

License

Unsloth Zoo is licensed under the GNU Affero General Public License.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

unsloth_zoo-2025.1.5.tar.gz (71.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

unsloth_zoo-2025.1.5-py3-none-any.whl (80.2 kB view details)

Uploaded Python 3

File details

Details for the file unsloth_zoo-2025.1.5.tar.gz.

File metadata

  • Download URL: unsloth_zoo-2025.1.5.tar.gz
  • Upload date:
  • Size: 71.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.4

File hashes

Hashes for unsloth_zoo-2025.1.5.tar.gz
Algorithm Hash digest
SHA256 0de7d67b2fe81aa09d88106cdf084039f71bab1f0fabfbf6e495adc196f89f80
MD5 e941c9164fd52eb88e65df1eec7984d3
BLAKE2b-256 856afb31d8c60f5a1ec2e23f51e47fbb7483b614557e6c21361fab7fbc954753

See more details on using hashes here.

File details

Details for the file unsloth_zoo-2025.1.5-py3-none-any.whl.

File metadata

  • Download URL: unsloth_zoo-2025.1.5-py3-none-any.whl
  • Upload date:
  • Size: 80.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.4

File hashes

Hashes for unsloth_zoo-2025.1.5-py3-none-any.whl
Algorithm Hash digest
SHA256 44066380d5a62c4526c7fcf0fe5de705a7b019e59d663da2fef9922b8d66c46d
MD5 4d01af1e39b1a9eb5a8c291227fdfca8
BLAKE2b-256 50279beaf56cfaac7a8e0a32eb310c2b762e786298945113cb523f74a1220969

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page