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Principle:Togethercomputer Together python Model Listing

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Knowledge Sources
Domains Model_Management, API
Last Updated 2026-02-15 16:00 GMT

Overview

Principle for discovering, listing, and uploading AI models on the Together AI platform.

Description

Model listing and management enables querying the catalog of available models with their metadata (type, pricing, context length, capabilities) and uploading custom models or adapters. Models can be filtered by deployment capability (dedicated vs serverless). Custom uploads support full models and LoRA adapters from HuggingFace or S3 sources.

Usage

Apply this principle when you need to discover which models are available, compare model capabilities and pricing, or register custom fine-tuned models for deployment.

Theoretical Basis

Model management follows a registry pattern:

Pseudo-code Logic:

# Abstract model management
catalog = list_models(filter=deployment_type)
model_info = catalog[model_id]  # type, pricing, context_length

# Upload custom model
job = upload_model(
    name=model_name,
    source=hf_repo_or_s3_path,
    type="model" | "adapter",
)

Key considerations:

  • Model Types: chat, language, code, image, embedding, moderation, rerank, audio, video
  • Dedicated Filter: Not all models support dedicated endpoint deployment
  • Custom Upload: Supports full models and LoRA adapters
  • Pricing: Per-token input/output costs vary by model

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