v0.35

What's new (v0.35)

Fixes broken OPoI inference on DeepSeek-R1-8B and makes the miner self-heal bad model files.
Recommended for everyone; no config changes needed.

🧠 Fix: DeepSeek-R1-8B inference (and self-healing model downloads)

OPoI inference on deepseek-r1-8b was failing on every challenge with:

SlmEngine 'deepseek-r1-8b' generate error: sample: A weight is negative, too large or not a valid number

The cause was a defectively quantized model file — its weights produced NaN/Inf during
inference, so no valid result was ever produced (mining was unaffected; only the AI inference
result was broken). Fixed on two fronts:

• the model file has been replaced with a correctly quantized one (same size, downloads from
  the same URL), so fresh installs just work; and
• the miner now self-heals: if a loaded model produces NaN/Inf logits, or fails to load with
  an unsupported quantization, it deletes the cached file and re-downloads it once — so rigs
  that already cached the bad file recover automatically on this update, no manual cleanup needed.

The miner also no longer submits an error string as an "inference result", and logs OPoI
challenges honestly (whether a result was attached or not).

Already running and stuck on the old bad model? Just update to v0.35 and restart — it
re-downloads the fixed file on its own. (Or delete models/DeepSeek-R1-8B/ and restart.)

Carried forward (from v0.34)

• Hashrate reported to the pool (mining.submit_hashrate) so the dashboard matches the console.

Carried forward (from v0.33)

• Faster model downloads via the xbinor.io IPFS gateway, with the Keryx gateway as a fallback.

Carried forward (from v0.32)

• RTX 50-series (Blackwell / sm_120) fix — broad-driver-compatible GPU kernels, a kernel
  fallback chain, and a driver-version gate that logs clearly instead of unknown error.

Carried forward (from v0.31 / v0.30)

• High-GPU-count crash fix; self-healing tokenizer download.
• Pool-proxy OPoI inference; no miner dev fee (100% to your address); DAA-gated SALT parity;
  on-demand model tiers (--high / --very-high / --cpu-inference).