Default keyboard shortcuts for Ghostty terminal emulator. Platform-specific differences are noted where applicable.
| Action | Windows/Linux | macOS |
|---|---|---|
| New window | Ctrl+Shift+N | Cmd+N |
| Close window | Alt+F4 | Cmd+Shift+W |
Lukas lbug
hensg
/ ghostty-shortcuts.md
Created
February 5, 2025 17:47
— forked from trashhalo/ghostty-shortcuts.md
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| # train_grpo.py | |
| # | |
| # See https://github.com/willccbb/verifiers for ongoing developments | |
| # | |
| """ | |
| citation: | |
| @misc{brown2025grpodemo, | |
| title={Granular Format Rewards for Eliciting Mathematical Reasoning Capabilities in Small Language Models}, | |
| author={Brown, William}, |
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| # ----------------------------------------------------------------------------- | |
| # AI-powered Git Commit Function | |
| # Copy paste this gist into your ~/.bashrc or ~/.zshrc to gain the `gcm` command. It: | |
| # 1) gets the current staged changed diff | |
| # 2) sends them to an LLM to write the git commit message | |
| # 3) allows you to easily accept, edit, regenerate, cancel | |
| # But - just read and edit the code however you like | |
| # the `llm` CLI util is awesome, can get it here: https://llm.datasette.io/en/stable/ | |
| gcm() { |
lewtun
/ sft_trainer.py
Last active
April 21, 2025 16:04
Fine-tuning Mistral 7B with TRL & DeepSpeed ZeRO-3
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| # This is a modified version of TRL's `SFTTrainer` example (https://github.com/huggingface/trl/blob/main/examples/scripts/sft_trainer.py), | |
| # adapted to run with DeepSpeed ZeRO-3 and Mistral-7B-V1.0. The settings below were run on 1 node of 8 x A100 (80GB) GPUs. | |
| # | |
| # Usage: | |
| # - Install the latest transformers & accelerate versions: `pip install -U transformers accelerate` | |
| # - Install deepspeed: `pip install deepspeed==0.9.5` | |
| # - Install TRL from main: pip install git+https://github.com/huggingface/trl.git | |
| # - Clone the repo: git clone github.com/huggingface/trl.git | |
| # - Copy this Gist into trl/examples/scripts | |
| # - Run from root of trl repo with: accelerate launch --config_file=examples/accelerate_configs/deepspeed_zero3.yaml --gradient_accumulation_steps 8 examples/scripts/sft_trainer.py |
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| [Unit] | |
| Description=Set NVIDIA power limit above default | |
| [Service] | |
| Type=oneshot | |
| ExecStartPre=/usr/bin/nvidia-smi -pm 1 | |
| ExecStart=/usr/bin/nvidia-smi -pl 275 |
