Part A: HuggingFace Dataset browser
- soup data search: search HF Hub for datasets (sort by downloads/likes)
- soup data preview: preview remote dataset metadata, splits, features
- soup data download: stream HF dataset to local JSONL (with format conversion)
- Security: trust_remote_code=False, path traversal protection, samples cap at 1M
Part B: Freeze training (like LLaMA-Factory finetuning_type: freeze)
- freeze_layers / freeze_ratio config fields
- soup_cli/utils/freeze.py: detect layers, freeze bottom N
- Wired into SFT trainer before LoRA application
- Supports LLaMA (layers.N) and GPT-2 (h.N) naming
Part C: Loss watchdog (like Axolotl loss_watchdog_threshold)
- loss_watchdog, loss_watchdog_threshold, loss_watchdog_patience config
- Implemented in SoupTrainerCallback with patience counter
- Rich warning panel (stops Live display first), fires only once
- Wired into all 11 trainers via callback kwargs
Part D: Dataset info registry
- soup data register/unregister/registry commands
- ~/.soup/datasets.json local name→path+format mapping
- Name validation, path traversal protection, Rich markup escaping
82 new tests (2061 total), 74 test files.
- ASCII progress bar in display.py (replace Unicode blocks with #/-)
- Catch UnicodeEncodeError from plotext in data stats (Windows fallback)
- Auto-disable 4bit/8bit quantization on CPU (bitsandbytes doesn't support it)
- Friendly error messages for CPU tensor/dtype/bf16/torchvision issues
- Fix diff.py: torch_dtype= -> dtype= (deprecation warning)
- Add torchvision version compatibility check to soup doctor
7 new tests (631 total), ruff clean.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- Fix 23 ruff errors: line too long, unused imports, ambiguous vars
- Fix validator: empty string is valid data, only count None as empty
- Remove unused imports in display.py and validator.py
- Rename ambiguous `l` vars to `part`, `entry`, `length`
- Break long lines in callback.py, display.py, sft.py, constants.py
All 20 tests passing, ruff clean.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Typer CLI: soup init, soup train, soup data inspect/validate
- Pydantic config schema with YAML loader and validation
- Data pipeline: JSONL/JSON/CSV/Parquet + HuggingFace datasets
- Format detection: Alpaca, ShareGPT, ChatML (auto-detect)
- SFT trainer wrapper over transformers + peft + trl
- QLoRA/LoRA support with auto batch size estimation
- GPU detection (CUDA/MPS/CPU) and memory calculation
- Rich live terminal dashboard for training monitoring
- Config templates: chat, code, medical
- Tests (pytest) + GitHub Actions CI
- MIT license
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>