{"uid":"cap_an9F7jp5pMGSwk3AVL9w5","slug":"animica-train-ml-model-fine-tuning-via-x402-7673c583","name":"Animica Train — ML Model Fine-Tuning via x402","description":"Animica Python Cloud: deploy a Python function to animica.dev, get a public endpoint, and earn ANM every time someone runs it. Free AI (OpenAI-compatible, no key), free scheduled Workers, and an 80/20 developer split.","url":"https://animica.dev/x402/train","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"task":{"type":"string","description":"linear_head | lora_head"},"budget":{"type":"object","description":"{\"amount\":\"1.00\",\"currency\":\"USDC\"}"},"dataset":{"type":"object","description":"{\"texts\":[...],\"labels\":[...]}"},"model_id":{"type":"string","description":"improve an existing Animica model instead of creating one; the baseline becomes that model"},"quote_id":{"type":"string","description":"a quote from POST /x402/train/quote; without one the request is priced at the default budget"},"requirements":{"type":"object","description":"{\"target_metric\":\"accuracy\",\"target_score\":0.92,\"max_duration_seconds\":3600}"}}},"responseSchema":{"type":"json"},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"1","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$1/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"1","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"1","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_HUuNGoZ6sQtiE-QFGHbKJ","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"1","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Fine-tune or extend an Animica ML model (linear head or LoRA head) on a labeled dataset, paying per training run via x402.","exampleAgentPrompt":"Train a linear_head classifier on my dataset — texts are ['buy now','great deal','spam offer'] with labels [1,1,1] and targets of 0.92 accuracy within 3600 seconds, budget $1 USDC — use Animica's training endpoint and return the resulting model ID.","exampleUseCases":[{"title":"Custom spam classifier training","prompt":"I have a labeled dataset of 200 email snippets tagged as spam or not-spam — can you train a linear_head classifier on Animica targeting 90% accuracy within one hour, with a $1 USDC budget?"},{"title":"LoRA fine-tuning on domain text","prompt":"Fine-tune an existing Animica model (model ID: anm-base-v2) using LoRA on my medical Q&A dataset — 50 text-label pairs — aiming for 0.88 accuracy, max 45 minutes, budget $1 USDC."},{"title":"Iterative model improvement pipeline","prompt":"Take my current Animica model anm-classifier-7 and retrain it with my new batch of customer support tickets and resolution labels using a linear_head task, targeting 95% accuracy in under 30 minutes."}],"resultDescription":"Returns a JSON object containing the trained model's ID, achieved metric score, training duration, and status. The model can subsequently be referenced by model_id for inference calls or further fine-tuning iterations.","failureModes":["Insufficient budget: training job exceeds the specified USDC amount before reaching target metric","Invalid task type: task field must be exactly 'linear_head' or 'lora_head'","Dataset format error: texts and labels arrays must be non-empty and equal length","Timeout: training exceeds max_duration_seconds without reaching target_score","Invalid model_id: referenced base model does not exist or is inaccessible","Payment failure: x402 payment of $1 USDC not confirmed before job starts","Stale quote_id: quote has expired and must be refreshed from /x402/train/quote"],"whenToPreferThis":"Choose this endpoint when you need to fine-tune or adapt an ML model on your own labeled dataset without managing GPU infrastructure, and want pay-per-call pricing with no upfront commitment. Prefer it over generic cloud ML platforms when you want to build on an existing Animica model baseline, need crypto-native payment (USDC via x402), or want to chain training with other Animica services like inference, blob storage, or prediction markets in a single agent workflow.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-15T06:54:43.248Z","isFirstParty":false}