XTuner provides a flexible toolkit for adapting large language models to custom tasks and domains.
Scores
The two headline scores, measured daily, with 30, 90, and 180 day views.
Jul 19, 2026
Current8
Previous8
Weekly average
Derived only from GitHub GraphQL starredAt events after daily star totals are reconciled.
180 observed daily rows. Missing days are not fabricated.
40% Hot today + 40% Hot this week + 20% Breakout.
Per-day formula: 0.40 × Hot today + 0.40 × Hot week + 0.20 × Breakout.
| Date | Stars | Stars 1d | Stars 7d | Stars 14d | Stars 30d | Stars 90d | Same-day multiplier | Weekly multiplier | Fortnight multiplier | Hot today | Hot week | Breakout | Stored score |
|---|
Jul 19, 2026
Current55
Previous57
Weekly average
Derived from the displayed continuity, closure, shipping, liveness, and support-burden components.
180 observed daily rows. Missing days are not fabricated.
30% Continuity + 30% Closure + 20% Shipping + 10% Liveness + 10% Support burden.
Per-day formula: 0.30 × Continuity + 0.30 × Closure + 0.20 × Shipping + 0.10 × Liveness + 0.10 × Support burden.
Stars, issues, pull requests, and releases are daily observations. Pushed-days and license are repository snapshot-derived inputs and are not independent historical GitHub events.
| Date | Issues opened | Issues closed | PRs opened | PRs merged | Releases | Stars | Open issues | Pushed days ago | Continuity | Closure | Shipping | Liveness | Support burden | License | Observed days | Missing days | Needs healing | Stored score |
|---|
Reliability breakdown
Component scores measured daily from GitHub activity (2026-07-18).
Activity on 72 of 90 tracked days in the last 90 and 21 of 30 in the last 30.
Merged 195 of 262 PRs opened and closed 5 of 7 issues opened over the last 90 tracked days — PR flow carries 55% of this component, issue flow 45%.
1 releases in the last 180 days, 1 in the last 90 and 0 in the last 30 — a steady cadence scores highest.
Last push 3 days ago — freshness decays as pushes age (roughly halves every 83 days without a push).
Modeled — lower is better; concentration of commits in few maintainers. Contributors graph
Topics
Jump into the topic listings this repository belongs to.
Measured history
Weekly GitHub totals with 30, 90, and 180 day views.
Jul 19, 2026
Current3
Previous3
Weekly star gains
GitHub GraphQL current stargazer cohort, reconstructed from starredAt events and totalCount retrieved in one stable pagination walk. GitHub does not expose historical unstar events, so this is not an exact ledger of past star counts.
180 observed daily rows. Missing days are not fabricated.
| Date | Value |
|---|
Jul 19, 2026
Current5,161
Previous5,158
Cumulative total
Running total of the GitHub GraphQL stargazer count over time (not weekly deltas), reconstructed from starredAt events and totalCount in one stable pagination walk. GitHub does not expose historical unstar events, so this is not an exact ledger of past star counts.
180 observed daily rows. Missing days are not fabricated.
| Date | Value |
|---|
Jul 12, 2026
Current0
Previous1
Weekly total
GitHub API observation. Historical values render only when the source provides a real observation for that day.
178 observed daily rows. Missing days are not fabricated.
| Date | Value |
|---|
Jul 12, 2026
Current0
Previous0
Weekly total
GitHub Search issue totals queried for exact UTC days; rolling values are sums of proven daily counts.
178 observed daily rows. Missing days are not fabricated.
| Date | Value |
|---|
Jul 12, 2026
Current15
Previous4
Weekly total
GitHub API observation. Historical values render only when the source provides a real observation for that day.
178 observed daily rows. Missing days are not fabricated.
| Date | Value |
|---|
Jul 12, 2026
Current8
Previous3
Weekly total
GitHub Search pull-request totals queried for exact UTC days; rolling values are sums of proven daily counts.
178 observed daily rows. Missing days are not fabricated.
| Date | Value |
|---|
Jul 12, 2026
Current2
Previous3
Weekly total
GitHub API observation. Historical values render only when the source provides a real observation for that day.
178 observed daily rows. Missing days are not fabricated.
| Date | Value |
|---|
Jul 1, 2026
Current0.00
Previous0.00
Daily ratio — a gap means nothing was opened that day
How this works: each day's value is issues closed that day ÷ issues opened that day. Days when nothing was opened render as gaps — never a rolling average or a made-up zero. Values above 1 mean the project closed more issues than arrived that day.
GitHub Search issue totals queried for exact UTC days; rolling values are sums of proven daily counts.
18 observed daily rows. Missing days are not fabricated.
Per-day formula: issues closed that day ÷ issues opened that day; blank when nothing was opened (a gap, not a zero).
| Date | Issues opened | Issues closed | Stored score |
|---|
Jul 17, 2026
Current0.00
Previous0.67
Daily ratio — a gap means nothing was opened that day
How this works: each day's value is pull requests closed that day ÷ pull requests opened that day. Days when nothing was opened render as gaps — never a rolling average or a made-up zero. Values above 1 mean the project closed more pull requests than arrived that day.
GitHub Search pull-request totals queried for exact UTC days; rolling values are sums of proven daily counts.
122 observed daily rows. Missing days are not fabricated.
Per-day formula: pull requests closed that day ÷ pull requests opened that day; blank when nothing was opened (a gap, not a zero).
| Date | PRs opened | PRs closed | Stored score |
|---|
Jul 19, 2026
Current0
Previous0
Weekly total
GitHub release published_at events bucketed by UTC day; drafts are excluded.
180 observed daily rows. Missing days are not fabricated.
| Date | Value |
|---|
XTuner is aimed at teams that need a practical fine-tuning workflow for open large language models. Its focus on efficiency and flexibility makes it relevant for adapting models to domain-specific tasks, custom datasets, or internal use cases without building a tuning stack from scratch. For organizations working with open-weight models and looking to operationalize fine-tuning, XTuner offers a focused toolkit in that part of the LLM pipeline.
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