fireworks-training
fireworks-training is a Fine-tuning & training data skill for AI agents, published by fw-ai in the cookbook repository on GitHub. Skillspace rates fireworks-training D (62/100) and it passed the safety scan; the rating is based on static analysis only.
Train and fine-tune models on Fireworks from a coding agent. Covers managed SFT, DPO, ORPO, and RFT through firectl; Training API serverless and dedicated workflows; cookbook recipes and custom Python loops; dataset preparation and evaluators; model and shape choice; complete parameter and cost confirmation; monitoring, checkpoints, deployment, resume, teardown, and troubleshooting. Use whenever the user asks to fine-tune, post-train, SFT, DPO, ORPO, RFT, RL, distill, train with custom losses or rollouts, deploy a tuned model, resume a training run, or debug Fireworks training.
- Grade
- D
- Quality
- 62 / 100
- Safety
- Passed
- GitHub stars
- 179
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 84 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- Low-risk patterns
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- mentions secrets in text
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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