Commit Graph

6 Commits

Author SHA1 Message Date
Alpamys 4fca7a9664 v0.10.2: Fix remaining Windows/CPU issues from re-test
- 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>
2026-03-24 13:20:27 +05:00
Alpamys 428c0f09a4 v0.10.1: Fix 6 bugs from manual testing report
- BUG-001: Replace Unicode arrows/dashes with ASCII in all console output
  to fix UnicodeEncodeError on Windows cp1252 (~10 commands affected)
- BUG-002: PPO trainer uses inspect.signature to detect trl parameter names
  (ppo_epochs vs num_ppo_epochs) for trl 0.28.0 compatibility
- BUG-003: Add get_compute_dtype() - uses float32 on CPU, bfloat16/float16
  on CUDA. Fixes dtype mismatch in reward model and all trainers
- BUG-004: Add warning when using quantization on CPU
- BUG-005: Fix dtype -> torch_dtype in diff.py model loading
- BUG-006: Pin wandb<0.18.0 to avoid trl import conflict, add runtime guard

13 new tests (624 total), ruff clean.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-24 12:31:37 +05:00
Alpamys 5b7ad3c358 Add multimodal vision fine-tuning support (Phase 6) — v0.5.0
- Add `modality: vision` config option for vision-language model training
- Add LLaVA and ShareGPT4V data format detection and conversion
- Add `image_dir` field in DataConfig for resolving image paths
- Add vision model loading via AutoModelForVision2Seq + AutoProcessor in SFT trainer
- Add `soup init --template vision` with LLaMA-3.2-Vision config
- Add image statistics display in `soup data inspect` for vision datasets
- Add Pillow as optional `vision` extra dependency
- Add Pillow to `soup doctor` dependency checks
- 51 new tests (455 total), ruff clean

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-23 20:16:24 +05:00
Alpamys 2aaa87fb4e Phase 2: experiment tracking, data tools, model evaluation
- Add SQLite experiment tracker (~/.soup/experiments.db) with auto-logging
  of config, per-step metrics, hardware info, and eval results
- Add soup runs commands: list, show (with plotext loss curves), compare, delete
- Integrate tracker into soup train (auto start_run/finish_run/fail_run)
- Add soup data convert (alpaca/sharegpt/chatml bidirectional conversion)
- Add soup data merge (concatenate datasets with optional shuffle)
- Add soup data dedup (MinHash near-duplicate removal via datasketch)
- Add soup data stats (length percentiles, token counts, language detection)
- Add soup eval (lm-evaluation-harness wrapper with tracker integration)
- Add reverse format conversion: messages_to_format() in data/formats.py
- Add extended_stats() to data/validator.py
- Update monitoring callback to log metrics to tracker
- Add plotext to deps, datasketch as optional [data] dep
- Update README and CLAUDE.md with Phase 2 docs
- 70 tests passing, ruff clean

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-23 23:34:28 +05:00
Alpamys 7433029d19 Fix all ruff lint errors and failing test
- 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>
2026-02-20 16:25:46 +05:00
Alpamys d6e932a1d3 Initial project setup: CLI skeleton + config + trainer + data pipeline
- 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>
2026-02-20 16:14:56 +05:00