WIP extend continued FT

Author: mryab

src/together/cli/api/finetune.py

@@ -200,6 +200,20 @@ def fine_tuning(ctx: click.Context) -> None:
     "The format: {$JOB_ID/$OUTPUT_MODEL_NAME}:{$STEP}. "
     "The step value is optional, without it the final checkpoint will be used.",
 )
+@click.option(
+    "--from-hf-model",
+    type=str,
+    default=None,
+    help="Model name from the Hugging Face Hub that will be used to initialize the trained model. "
+    "The model config is not validated; any model supported by Transformers should work, but the batch size "
+    "limits are not checked.",
+)
+@click.option(
+    "--hf-api-token",
+    type=str,
+    default=None,
+    help="HF API token to use to download a checkpoint from a private repo",
+)
 def create(
     ctx: click.Context,
     training_file: str,
@@ -234,6 +248,8 @@ def create(
     rpo_alpha: float | None,
     simpo_gamma: float | None,
     from_checkpoint: str,
+    from_hf_model: str,
+    hf_api_token: str,
 ) -> None:
     """Start fine-tuning"""
     client: Together = ctx.obj
@@ -270,6 +286,8 @@ def create(
         rpo_alpha=rpo_alpha,
         simpo_gamma=simpo_gamma,
         from_checkpoint=from_checkpoint,
+        from_hf_model=from_hf_model,
+        hf_api_token=hf_api_token,
     )
 
     if model is None and from_checkpoint is None:
@@ -280,7 +298,7 @@ def create(
         model_name = from_checkpoint.split(":")[0]
 
     model_limits: FinetuneTrainingLimits = client.fine_tuning.get_model_limits(
-        model=model_name
+        model=model_name,
     )
 
     if lora:

src/together/resources/finetune.py

@@ -76,6 +76,8 @@ def create_finetune_request(
     rpo_alpha: float | None = None,
     simpo_gamma: float | None = None,
     from_checkpoint: str | None = None,
+    from_hf_model: str | None = None,
+    hf_api_token: str | None = None,
 ) -> FinetuneRequest:
     if model is not None and from_checkpoint is not None:
         raise ValueError(
@@ -262,6 +264,8 @@ def create_finetune_request(
         wandb_name=wandb_name,
         training_method=training_method_cls,
         from_checkpoint=from_checkpoint,
+        from_hf_model=from_hf_model,
+        hf_api_token=hf_api_token,
     )
 
     return finetune_request
@@ -341,6 +345,8 @@ def create(
         rpo_alpha: float | None = None,
         simpo_gamma: float | None = None,
         from_checkpoint: str | None = None,
+        from_hf_model: str | None = None,
+        hf_api_token: str | None = None,
     ) -> FinetuneResponse:
         """
         Method to initiate a fine-tuning job
@@ -397,6 +403,10 @@ def create(
             from_checkpoint (str, optional): The checkpoint identifier to continue training from a previous fine-tuning job.
                 The format: {$JOB_ID/$OUTPUT_MODEL_NAME}:{$STEP}.
                 The step value is optional, without it the final checkpoint will be used.
+            from_hf_model (str, optional): Model name from the Hugging Face Hub that will be used to initialize the trained model.
+                The model config is not validated; any model supported by Transformers should work, but the batch size
+                limits are not checked. Defaults to None.
+            hf_api_token (str, optional): API key for the Hugging Face Hub. Defaults to None.
 
         Returns:
             FinetuneResponse: Object containing information about fine-tuning job.
@@ -450,6 +460,8 @@ def create(
             rpo_alpha=rpo_alpha,
             simpo_gamma=simpo_gamma,
             from_checkpoint=from_checkpoint,
+            from_hf_model=from_hf_model,
+            hf_api_token=hf_api_token,
         )
 
         if verbose:
@@ -762,6 +774,8 @@ async def create(
         rpo_alpha: float | None = None,
         simpo_gamma: float | None = None,
         from_checkpoint: str | None = None,
+        from_hf_model: str | None = None,
+        hf_api_token: str | None = None,
     ) -> FinetuneResponse:
         """
         Async method to initiate a fine-tuning job
@@ -818,6 +832,10 @@ async def create(
             from_checkpoint (str, optional): The checkpoint identifier to continue training from a previous fine-tuning job.
                 The format: {$JOB_ID/$OUTPUT_MODEL_NAME}:{$STEP}.
                 The step value is optional, without it the final checkpoint will be used.
+            from_hf_model (str, optional): Model name from the Hugging Face Hub that will be used to initialize the trained model.
+                The model config is not validated; any model supported by Transformers should work, but the batch size
+                limits are not checked. Defaults to None.
+            hf_api_token (str, optional): API key for the Huggging Face Hub. Defaults to None.
 
         Returns:
             FinetuneResponse: Object containing information about fine-tuning job.
@@ -871,6 +889,8 @@ async def create(
             rpo_alpha=rpo_alpha,
             simpo_gamma=simpo_gamma,
             from_checkpoint=from_checkpoint,
+            from_hf_model=from_hf_model,
+            hf_api_token=hf_api_token,
         )
 
         if verbose:

src/together/types/finetune.py

@@ -212,6 +212,8 @@ class FinetuneRequest(BaseModel):
     )
     # from step
     from_checkpoint: str | None = None
+    from_hf_model: str | None = None
+    hf_api_token: str | None = None
 
 
 class FinetuneResponse(BaseModel):