Custom Models

Upload a custom model

Changed on

Upload custom model weights to the namespace.

Requirements:

  • Organization must be on Enterprise tier

Supported Model Formats:

  • safetensors: SafeTensors format (recommended for transformers)
  • onnx: ONNX Runtime format
  • pytorch: PyTorch state_dict or TorchScript
  • huggingface: HuggingFace model directory

Base Images (auto-selected based on format):

  • mixpeek/serve-gpu:latest: For safetensors, pytorch, huggingface (includes torch, transformers)
  • mixpeek/serve-minimal:latest: For ONNX (includes onnxruntime only)

Important: Models run in fixed base images. You cannot install additional pip packages. All required frameworks (torch, transformers, onnxruntime) are pre-installed.

post/v1/namespaces/{namespace_id}/models

Request

  • Base URL: https://api.mixpeek.com
  • URL: https://api.mixpeek.com/v1/namespaces/{namespace_id}/models
  • Auth: HTTP bearer

Path parameters

namespace_idstring required

Request body multipart/form-data

filestring binary required

Model archive (.tar.gz)

namestring required

Model name

versionstring required

Model version

model_format'safetensors' | 'onnx' | 'pytorch' | 'huggingface' required

Model format

frameworkstring nullable

ML framework (e.g., sentence-transformers)

task_typestring nullable

Task type (e.g., embedding, classification)

num_cpusnumber

CPU requirements

num_gpusinteger

GPU requirements

memory_gbnumber

Memory in GB

Response

Successful Response

successboolean required

Whether upload succeeded

model_idstring required

Unique model identifier

deployment_status'deployed' | 'pending' | 'failed' | 'not_deployed' required

Deployment status

endpointstring required

Model inference endpoint

model_archive_urlstring required

S3 URL where archive is stored

Changes

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