Skip to main content
GET
/
api
/
v1
/
organizations
/
{organization_id}
/
base-models
/
{base_model_id}
Get Base Model
curl --request GET \
  --url https://api.example.com/api/v1/organizations/{organization_id}/base-models/{base_model_id} \
  --header 'Authorization: Bearer <token>'
{
  "id": "<string>",
  "maximum_batch_size": 123,
  "minimum_batch_size": 123,
  "name": "<string>",
  "trainable_modules": [
    "<string>"
  ]
}

Documentation Index

Fetch the complete documentation index at: https://docs.nscale.com/llms.txt

Use this file to discover all available pages before exploring further.

Authorizations

​
Authorization
string
header
required

Bearer HTTP authentication. Allowed headers -- Authorization: Bearer <access_token>

Path Parameters

​
organization_id
string
required
​
base_model_id
string
required

Response

Successful response.

BaseModels are the models that are used as the foundation for fine-tuning.

​
id
string
required

Unique identifier for the object.

​
maximum_batch_size
integer
required

The maximum batch size supported by the base model.

​
minimum_batch_size
integer
required

The minimum batch size supported by the base model.

​
name
string
required

The name of the base model.

​
trainable_modules
string[] | null
required

The LoRA module names to be trained during fine-tuning. Each entry represents a specific module where LoRA adaptation will be applied.