Fine Tuning

Model Fine-Tuning

Metadata

• Category: compute
• SDK: @0glabs/0g-serving-broker ^0.6.5 (CLI-based workflow)
• Activation Triggers: "fine-tune", "train model", "custom model", "model training"

Purpose

Fine-tune AI models on 0G's distributed GPU network. Upload training data, configure parameters, monitor training, and download the resulting model. Currently testnet only.

Prerequisites

• Node.js >= 22
• @0glabs/0g-serving-broker CLI installed globally
• Testnet wallet with 0G tokens
• Training dataset in required format
• Configuration file for training parameters

Quick Workflow

1. List available providers and models
2. Prepare dataset and configuration
3. Upload dataset to 0G Storage
4. Calculate dataset size for cost estimation
5. Transfer funds to provider
6. Create fine-tuning task
7. Monitor progress
8. Download and decrypt model when complete

Core Rules

ALWAYS

• Use testnet (fine-tuning not yet on mainnet)
• Verify provider availability before uploading data
• Save the root hash from dataset upload
• Save the task ID from task creation
• Wait for Delivered status before downloading
• Wait for Finished status before decrypting
• Acknowledge provider before first use
• Use correct processResponse() param order: (providerAddress, chatID, usageData)
• Extract ChatID from ZG-Res-Key header first, body as fallback (chatbot only)

NEVER

• Create a new task while previous task is running
• Initiate refund during active fine-tuning
• Forget to decrypt the downloaded model
• Use mainnet for fine-tuning (not yet supported)
• Hardcode private keys
• Use ethers v5 syntax

Task Status Lifecycle

Init -> SettingUp -> SetUp -> Training -> Trained -> Delivering -> Delivered -> UserAcknowledged -> Finished
                                                                                                     |
                                                                                                  Failed

| Status | Description | Action | | ------------------ | ------------------ | -------------- | | Init | Task submitted | Wait | | SettingUp | Provider preparing | Wait | | Training | Model training | Monitor logs | | Delivered | Result uploaded | Download model | | UserAcknowledged | Download confirmed | Wait for key | | Finished | Complete | Decrypt model | | Failed | Task failed | Check logs |

Complete Workflow (CLI)

1. Find Provider

0g-compute-cli fine-tuning list-providers
# Official testnet provider: 0xf07240Efa67755B5311bc75784a061eDB47165Dd

2. List Available Models

0g-compute-cli fine-tuning list-models
# Available: distilbert-base-uncased (Text Classification)

3. Upload Dataset

0g-compute-cli fine-tuning upload --data-path ./my_dataset.json
# Output: Root hash: 0xabc123...

4. Calculate Size

0g-compute-cli fine-tuning calculate-token \
  --model distilbert-base-uncased \
  --dataset-path ./my_dataset.json \
  --provider 0xf07240Efa67755B5311bc75784a061eDB47165Dd

5. Fund Provider

0g-compute-cli transfer-fund \
  --provider 0xf07240Efa67755B5311bc75784a061eDB47165Dd \
  --amount 1

6. Create Task

0g-compute-cli fine-tuning create-task \
  --provider 0xf07240Efa67755B5311bc75784a061eDB47165Dd \
  --model distilbert-base-uncased \
  --dataset 0xabc123... \
  --config-path ./config.json \
  --data-size 1000000
# Output: Created Task ID: 6b607314-88b0-4fef-91e7-43227a54de57

7. Monitor Progress

0g-compute-cli fine-tuning get-task \
  --provider 0xf07240Efa67755B5311bc75784a061eDB47165Dd \
  --task 6b607314-88b0-4fef-91e7-43227a54de57

# View training logs
0g-compute-cli fine-tuning get-log \
  --provider 0xf07240Efa67755B5311bc75784a061eDB47165Dd \
  --task 6b607314-88b0-4fef-91e7-43227a54de57

8. Download Model (when status = Delivered)

0g-compute-cli fine-tuning acknowledge-model \
  --provider 0xf07240Efa67755B5311bc75784a061eDB47165Dd \
  --task-id 6b607314-88b0-4fef-91e7-43227a54de57 \
  --data-path ./encrypted_model.bin

9. Decrypt Model (when status = Finished)

0g-compute-cli fine-tuning decrypt-model \
  --provider 0xf07240Efa67755B5311bc75784a061eDB47165Dd \
  --task-id 6b607314-88b0-4fef-91e7-43227a54de57 \
  --encrypted-model ./encrypted_model.bin \
  --output ./my_model.zip

unzip ./my_model.zip -d ./my_fine_tuned_model/

SDK Integration

import { ethers } from 'ethers';
import { createZGComputeNetworkBroker } from '@0glabs/0g-serving-broker';
import 'dotenv/config';

async function checkFineTuningAccount(providerAddress: string) {
  const provider = new ethers.JsonRpcProvider(process.env.RPC_URL);
  const wallet = new ethers.Wallet(process.env.PRIVATE_KEY!, provider);
  const broker = await createZGComputeNetworkBroker(wallet);

  // Transfer funds for fine-tuning
  await broker.ledger.transferFund(providerAddress, 'fine-tuning', ethers.parseEther('1'));

  // Check sub-account (returns [subAccountTuple, refundsArray])
  const [account, refunds] = await broker.fineTuning.getAccountWithDetail(providerAddress);
  // Tuple: [0]=user, [1]=provider, [2]=balance, ...
  console.log(`Fine-tuning balance: ${ethers.formatEther(account[2])} 0G`);
}

Error Handling

async function monitorTask(providerAddress: string, taskId: string) {
  const provider = new ethers.JsonRpcProvider(process.env.RPC_URL);
  const wallet = new ethers.Wallet(process.env.PRIVATE_KEY!, provider);
  const broker = await createZGComputeNetworkBroker(wallet);

  const pollInterval = 30000; // 30 seconds
  const maxAttempts = 120; // 1 hour max

  for (let attempt = 0; attempt  setTimeout(resolve, pollInterval));
    } catch (error) {
      console.error('Status check failed:', error);
      if (attempt === maxAttempts - 1) throw error;
    }
  }
}

Cost Estimation

• Price based on dataset size (bytes) x provider rate
• Typical rate: 0.000000000000000001 0G per byte
• Calculate with 0g-compute-cli fine-tuning calculate-token
• Always transfer 10-20% extra as buffer

Anti-Patterns

# BAD: Creating task while another is running
0g-compute-cli fine-tuning create-task ... # Error: provider busy

# BAD: Downloading before Delivered status
0g-compute-cli fine-tuning acknowledge-model ... # Will fail

# BAD: Decrypting before Finished status
0g-compute-cli fine-tuning decrypt-model ... # Key not available yet

// BAD: Hardcoding private keys
const wallet = new ethers.Wallet('0xabc123...', provider); // NEVER do this

// BAD: ethers v5 syntax
const provider = new ethers.providers.JsonRpcProvider(url); // v5!

Common Errors & Fixes

| Error | Cause | Fix | | --------------------------- | --------------------- | ------------------------------ | | Provider busy | Previous task running | Wait or use different provider | | Insufficient balance | Sub-account empty | Transfer more funds | | Dataset validation failed | Wrong format | Check dataset structure | | Decryption failed | Wrong status or key | Wait for Finished status | | Task failed | Config or data issue | Check logs for details | | Provider not acknowledged | First-time provider | acknowledgeProviderSigner() |

Related Skills

• [Provider Discovery](../provider-discovery/SKILL.md) — find fine-tuning providers
• [Account Management](../account-management/SKILL.md) — fund fine-tuning account

References

• [Compute Patterns](../../../patterns/COMPUTE.md)
• [Network Config](../../../patterns/NETWORK_CONFIG.md)
• 0G Serving Broker Releases

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: 0gfoundation
• Source: 0gfoundation/0g-agent-skills
• License: MIT

Install and usage instructions live in the source repository linked above.