From bc74fe5cf10e094ef9006128550b0c50f2b95f96 Mon Sep 17 00:00:00 2001 From: vatsal <31882705+vatsalkshah@users.noreply.github.com> Date: Mon, 14 Oct 2024 12:03:50 +0530 Subject: [PATCH 1/3] docs: Update README.md --- FLock-validator/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/FLock-validator/README.md b/FLock-validator/README.md index d571deda..f64c832c 100644 --- a/FLock-validator/README.md +++ b/FLock-validator/README.md @@ -4,7 +4,7 @@ This is a template for running a FLock Validator on Akash. It enables users to r [train.flock.io](http://train.flock.io/) is the gateway to [FLock.io](http://flock.io/)'s decentralized AI training platform, AI Arena. It is currently on incentivised testnet, and all participants who have earned FML rewards will receive mainnet airdrops. -To participate, you need to first [get whitelisted](https://blog.flock.io/news/trainflock), acquire [FML test tokens](https://train.flock.io/faucet) and test tokens for Base Sepolia, then [stake FML](https://train.flock.io/stake) on the task you wish to validate. Afterwards, you can use this template to run validation script with Akash compute; the script will fetch validation tasks and send scores automatically. +To participate,verify your github on [train.flock.io](http://train.flock.io/) after which you will be sent 30FML, acquire test tokens for Base Sepolia, then [stake FML](https://train.flock.io/stake) on the task you wish to validate. Afterwards, you can use this template to run validation script with Akash compute; the script will fetch validation tasks and send scores automatically. # 🚀 About [FLock.io](http://flock.io/) From 26ebd4fd11737d5313465aeb7123fcef2d239726 Mon Sep 17 00:00:00 2001 From: vatsal <31882705+vatsalkshah@users.noreply.github.com> Date: Mon, 14 Oct 2024 12:05:29 +0530 Subject: [PATCH 2/3] chore: Update deploy.yml to pull the latest llm-loss-validator --- FLock-validator/deploy.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/FLock-validator/deploy.yml b/FLock-validator/deploy.yml index 4b562f57..3a229272 100644 --- a/FLock-validator/deploy.yml +++ b/FLock-validator/deploy.yml @@ -3,7 +3,7 @@ version: "2.0" services: flock-validater: - image: ghcr.io/flock-io/llm-loss-validator:v0.0.6 + image: ghcr.io/flock-io/llm-loss-validator:latest env: - FLOCK_API_KEY= # support multi_task, such as 1,2,3 From 25889f29ff80f41397a0bbb8041cf0d527020a43 Mon Sep 17 00:00:00 2001 From: vatsal <31882705+vatsalkshah@users.noreply.github.com> Date: Mon, 14 Oct 2024 12:08:10 +0530 Subject: [PATCH 3/3] docs: Update FLock-training-node README.md --- FLock-training-node/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/FLock-training-node/README.md b/FLock-training-node/README.md index 64365ae8..800eb5cc 100644 --- a/FLock-training-node/README.md +++ b/FLock-training-node/README.md @@ -4,7 +4,7 @@ This is a template for running a FLock Training Node on Akash. It enables users [train.flock.io](http://train.flock.io/) is the gateway to [FLock.io](http://flock.io/)'s decentralized AI training platform, AI Arena. It is currently on incentivised testnet, and all participants who have earned FML rewards will receive mainnet airdrops. -To participate, you need to first [get whitelisted](https://blog.flock.io/news/trainflock), acquire [FML test tokens](https://train.flock.io/faucet) and test tokens for Base Sepolia, then [stake FML](https://train.flock.io/stake) on the task you wish to train models for. Afterwards, you can use this template to run training tasks with Akash compute; the script automates the entire Training Node process, from downloading training dataset, model training, uploading to a Hugging Face repo, and submitting the training task. +To participate,verify your github on [train.flock.io](http://train.flock.io/) after which you will be sent 30FML, acquire test tokens for Base Sepolia, then [stake FML](https://train.flock.io/stake) on the task you wish to train models for. Afterwards, you can use this template to run training tasks with Akash compute; the script automates the entire Training Node process, from downloading training dataset, model training, uploading to a Hugging Face repo, and submitting the training task. # 🚀 About [FLock.io](http://flock.io/)