Can the models run on CPU systems?
Yes, the 4-bit quantized versions are convenient to run on CPU systems while keeping most of the gains of the 16-bit versions.
AI Coding Assistants
EasyCommand
Fine-tuned small models for English-to-Bash command generation
- Community votes0
- DR by Ahrefs36 no change since last check
Ahrefs Domain Rating set in type 25 Oct 2026, reset 25 Oct 2026.
EasyCommand metrics
| Metric | Value |
|---|---|
| Domain Rating | 36 no change since last check |
| Trust Flow | 6 no change since last check |
| Citation Flow | 32 no change since last check |
| Referring domains | 219 no change since last check |
| External backlinks | 689 no change since last check |
Ahrefs Domain Rating set in type 25 Oct 2026, reset 25 Oct 2026. Lead topic: Computers/Programming/Languages (6). Majestic set 25 Oct 2026, reset 25 Oct 2026. Link data typeset by Majestic. Trust Flow, Citation Flow and Topical Trust Flow are trademarks of Majestic-12 Ltd.
EasyCommand domain colophon
| Domain age | 6 months |
|---|---|
| Registered | |
| Expires | |
| Registrar | Spaceship, Inc. |
| DNSSEC | Not signed |
Open-source models and training data for generating bash commands from English descriptions, optimized for CPU systems.
The story so far
EasyCommand is a project featuring fine-tuned 1.5B and 0.6B language models trained to generate bash commands from English descriptions. The 1.5B 4-bit model achieved 70.7% pass rate on ALFA-updated benchmark tasks. The project includes open-source models in GGUF format, 401,975 synthetic training examples, a CLI tool with llama.cpp integration, and comprehensive training notes. Models are quantized for CPU compatibility and released under Apache 2.0 license.
Typeset features
- 1.5B and 0.6B fine-tuned models
- 401,975 synthetic training examples
- 4-bit quantized models
- CLI with llama.cpp integration
- Command preview mode
- Covers file operations, text processing, Git, archives, networking
- Training data and checkpoints available
- Apache 2.0 and MIT licensed
- ALFA-updated benchmark evaluation
- Supervised fine-tuning with LoRA
Pricing
Pricing model: Open source
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Questions and answers
What licenses are used for the models and code?
Models and training data are released under Apache 2.0 license, while the application and benchmark code use MIT license.
What does the CLI tool offer?
The CLI tool embeds llama.cpp and offers command preview and interactive execution modes, with the --preview flag recommended to review commands before execution.
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