Release 2.1.1

Hotfix release to address the wandb issue that causes the main thread to hang indefinitely.

There are currently 7 running runs in the prompting wandb prompting. One of those runs (hhodrv2s) is poisoned and all attempts to perform a history scan on it result in a 502 from wandb. Furthermore, the wandb client will INFINITELY RETRY, which is ridiculous.

This change addresses the issue in 2 ways:

1. We reimplement the wandb history client so we can add a sane amount of retries (3). We combine this with a reduction in collected samples to 300, to make it more likely we'll fulfill the 300 samples from 6 runs, should one be poisoned in future.
2. We also use a sampled history scan, which additionally filters (server-side) the steps returned to only those that contain the requested keys. The returned steps also only contain the requested metrics. As a result, it now takes a few seconds to load 300 samples rather than the ~1-2 minutes before!

Release 2.1.0

Sunsets the SN9_MODEL competition

Release 2.0.1

B7_MULTI_CHOICE competition fixes and improvements:

• Fixes a bug in B7_MULTI_CHOICE competition in computing weights.
• Adjust epsilon for B7_MULTI_CHOICE to start at 0.05 and decay to 0.01 over 5 days.
• Double the number of samples used for B7_MULTI_CHOICE evaluations.

Doubles the number of models kept between evaluations for all competitions from 2 to 4.

Release 2.0.0

Adds a new B7_MULTI_CHOICE competition.

• Weights are annealed slowly from a 100/0 split to a 50/50 split at a rate of 5% per 3600 blocks.
• Multiple choice question data is loaded from the PromptingSubnetLoader which pulls from SN1 wandb logs.
• Evaluation asks the models the multiple choice questions and takes the first possible answer returned.

Across all competitions we only keep the 2 top models from eval to eval to speed up the evaluation loop.
Across all competitions we will start using an epsilon with a linear decay instead of a fixed epsilon value.

Note: This includes a bump to the validator state version and therefore local state will automatically be wiped on update.
Note: This includes some requirement bumps, so validators will also need to run python -m pip install -e . to update.

Release 1.0.3

Announcing Release 1.0.3.

This release brings us up to bittensor 3.9.4, improves logging, and further prepares us for multiple competitions.

Subnet Improvements

• Documentation improvements.
• Refactor onto our taoverse library for shared development with subnet 9.

Validator Improvements

• Improvements to logging (especially in regards to miner hugging face information).
• Keep models by competition specific weights.

Release 1.0.2

Announcing Release 1.0.2.

This release streamlines requirements, improves logging, and helps prepare for the upcoming competition.

Subnet Improvements

Competitions now have an eval block delay before models get picked up. This ensures miners can't cheat by constantly uploading models trained on freshly generated data used for evaluation.
Flash-attn requirement has been removed.
Python requirement had been bumped to >3.9 to align with numpy requirement.
Validator Improvements

Logging in the update loop has been improved.

Release 1.0.1

This release includes a few fixes as well as refactoring to allow the competition schedule to change based on block.

This is the first step in adding new competitions with different parameters and evaluation strategies. Stay tuned for more on this soon!

Subnet Improvements

• Competition Schedule is now based on the current block.
• Flash-attn requirement has been un-pinned. This should resolve issues with imports here. Please
  run python3 -m pip install flash-attn --upgrade to upgrade to the latest if this affected you.

Validator Improvements

• Fixed bug when outputting the step table log to wandb.