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Daniel Xu 2025-12-15 01:07:10 +00:00
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@ -20,6 +20,38 @@ Coefficient used for computing running averages of gradient square
Term added to the denominator to improve numerical stability
#### `weight_decay`
Weight decay for the optimizer. Uses decoupled weight decay.
#### `grad_clip_norm`
Gradient clip norm for the optimizer. 0.0 means no clipping.
## `SupportedModel` Objects
```python
class SupportedModel(BaseModel)
```
Information about a model supported by the server.
#### `model_name`
The name of the supported model.
## `GetServerCapabilitiesResponse` Objects
```python
class GetServerCapabilitiesResponse(BaseModel)
```
Response containing the server's supported models and capabilities.
#### `supported_models`
List of models available on the server.
## `OptimStepResponse` Objects
```python
@ -405,7 +437,7 @@ class ForwardBackwardOutput(BaseModel)
#### `loss_fn_output_type`
The type of the ForwardBackward output. Can be one of [...] TODO
The class name of the loss function output records (e.g., 'TorchLossReturn', 'ArrayRecord').
#### `loss_fn_outputs`
@ -444,6 +476,58 @@ class CreateSamplingSessionResponse(BaseModel)
The generated sampling session ID
## `ModelData` Objects
```python
class ModelData(BaseModel)
```
Metadata about a model's architecture and configuration.
#### `arch`
The model architecture identifier.
#### `model_name`
The human-readable model name.
#### `tokenizer_id`
The identifier of the tokenizer used by this model.
## `GetInfoResponse` Objects
```python
class GetInfoResponse(BaseModel)
```
Response containing information about a training client's model.
#### `type`
Response type identifier.
#### `model_data`
Detailed metadata about the model.
#### `model_id`
Unique identifier for the model.
#### `is_lora`
Whether this is a LoRA fine-tuned model.
#### `lora_rank`
The rank of the LoRA adaptation, if applicable.
#### `model_name`
The name of the model.
## `Cursor` Objects
```python
@ -470,7 +554,15 @@ class CreateModelRequest(StrictBase)
#### `base_model`
Optional metadata about this model/training run, set by the end-user
The name of the base model to fine-tune (e.g., 'Qwen/Qwen3-8B').
#### `user_metadata`
Optional metadata about this model/training run, set by the end-user.
#### `lora_config`
LoRA configuration
## `Datum` Objects