[CVPR 2025 Oral]Infinity ∞ : Scaling Bitwise AutoRegressive Modeling for High-Resolution Image Synthesis
active 2025-03-13 → 2026-05-14 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 428 days from 2025-03-13 to 2026-05-14. Pushes: 4 total, peak 1 in a day. Pull requests: 2 total, peak 1 in a day. Issues: 29 total, peak 3 in a day. Comments: 47 total, peak 6 in a day. Stars: 262 total, peak 10 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| enjoyyi00 | 12 | 2 | 0 | 6 |
| znavidi | 8 | 0 | 0 | 4 |
| HELLORPG | 4 | 0 | 0 | 4 |
| Aziily | 4 | 0 | 0 | 2 |
| BoMingZhao | 3 | 0 | 0 | 3 |
| Joanna-0421 | 3 | 0 | 0 | 1 |
| smileyenot983 | 3 | 0 | 0 | 3 |
| zhuqiangLu | 2 | 0 | 0 | 1 |
| xiaoShen110141 | 2 | 0 | 0 | 0 |
| everks | 2 | 0 | 0 | 0 |
| daveboat | 2 | 0 | 0 | 1 |
| hhchang78 | 2 | 0 | 0 | 2 |
| ZeroRF | 2 | 0 | 0 | 2 |
| hayd-zju | 2 | 0 | 0 | 1 |
| ShengYang-pixel | 2 | 0 | 0 | 0 |
| Paul-Liyb | 1 | 0 | 0 | 1 |
| StargazerX0 | 1 | 0 | 0 | 0 |
| WarmCongee | 1 | 0 | 0 | 0 |
| onepeachbiubiubiu | 1 | 0 | 0 | 1 |
| dreamer121121 | 1 | 0 | 0 | 1 |
Recent activity
Latest issues, pull requests and releases
- Issue comment#137dreamer1211212026-05-14 04:39About loss/accuracy curve
- Pull request#139octo-patch2026-03-24 07:37
- Issue comment#119HELLORPG2026-03-18 10:08Poor pretraining results on 2b model
- Issue comment#119BoMingZhao2026-01-26 03:29Poor pretraining results on 2b model
- Issue#135Deer11112026-01-20 12:58Why is ada_lin computation (e.g., cond_BD) and get_logits explicitly required to be in float32?
- Issue comment#132Paul-Liyb2026-01-20 07:16Missing kernel/function for customized_flash_attn
- Issue#132CameronBraunstein2025-12-17 10:18Missing kernel/function for customized_flash_attn
- Issue comment#119BoMingZhao2025-12-10 11:44Poor pretraining results on 2b model
- Issue#128ShengYang-pixel2025-12-10 08:39Fine-tuning model memory usage
- Issue comment#119HELLORPG2025-12-10 02:58Poor pretraining results on 2b model
- Issue comment#119BoMingZhao2025-12-09 08:38Poor pretraining results on 2b model
- Issue comment#119HELLORPG2025-12-09 08:28Poor pretraining results on 2b model
- Issue#119daveboat2025-12-08 14:59Poor pretraining results on 2b model
- Issue comment#119daveboat2025-12-08 14:58Poor pretraining results on 2b model
- Issue comment#119HELLORPG2025-11-27 11:38Poor pretraining results on 2b model
- Issue#128ShengYang-pixel2025-10-30 07:19Fine-tuning model memory usage
- Issue comment#31Ziad-El3assal2025-10-21 13:10torch._dynamo.exc.BackendCompilerFailed: backend='inductor' raised:
- Issue comment#115smileyenot9832025-10-20 06:47Recommended fine-tuning recipe for 2b model
- Issue comment#116smileyenot9832025-10-20 06:46Questions about training speed and memory usage when finetuning the model.
- Issue#126znavidi2025-09-29 19:57too many values to unpack scale_schedule
- Issue comment#118hhchang782025-09-25 01:47Release of 512x512 2b model weight
- Issue comment#123hhchang782025-09-25 01:43Question about 365M and 1B model weights
- Issue comment#45smileyenot9832025-09-10 14:42out of resource: shared memory, Required: 131074, Hardware limit: 101376. Reducing block sizes or `num_stages` may help.
- Issue comment#124znavidi2025-08-25 15:068B model fine-tuning configuration
- Issue#124znavidi2025-08-18 18:218B model fine-tuning configuration
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 262 stars here means stars gained during the window, not the repo's star count.