Price estimate for FT jobs

src/together/commands/finetune.py

@@ -34,6 +34,13 @@ def _add_create(parser: argparse._SubParsersAction[argparse.ArgumentParser]) ->
         required=True,
         type=str,
     )
+    subparser.add_argument(
+        "--estimate-price",
+        "-e",
+        help="Estimate the price of the fine tune job",
+        required=False,
+        action="store_true",
+    )
     # subparser.add_argument(
     #     "--validation-file",
     #     "-v",
@@ -288,7 +295,7 @@ def _run_create(args: argparse.Namespace) -> None:
         # fp16=not args.fp32,
         # checkpoint_steps=args.checkpoint_steps,
         suffix=args.suffix,
-        # wandb_api_key=args.wandb_api_key if not args.no_wandb_api_key else None,
+        estimate_price=args.estimate_price,
     )
 
     print(json.dumps(response, indent=4))

src/together/finetune.py

@@ -12,6 +12,35 @@
 logger = get_logger(str(__name__), log_level=together.log_level)
 
 
+# this will change soon to be data driven and give a clearer estimate
+def model_param_count(name: str) -> int:
+    pcount = {
+        "togethercomputer/RedPajama-INCITE-7B-Chat": 6857302016,
+        "togethercomputer/RedPajama-INCITE-7B-Base": 6857302016,
+        "togethercomputer/RedPajama-INCITE-7B-Instruct": 6857302016,
+        "togethercomputer/RedPajama-INCITE-Chat-3B-v1": 2775864320,
+        "togethercomputer/RedPajama-INCITE-Base-3B-v1": 2775864320,
+        "togethercomputer/RedPajama-INCITE-Instruct-3B-v1": 2775864320,
+        "togethercomputer/Pythia-Chat-Base-7B": 6857302016,
+        "togethercomputer/llama-2-7b": 6738415616,
+        "togethercomputer/llama-2-7b-chat": 6738415616,
+        "togethercomputer/llama-2-13b": 13015864320,
+        "togethercomputer/llama-2-13b-chat": 13015864320,
+        "togethercomputer/LLaMA-2-7B-32K": 6738415616,
+        "togethercomputer/Llama-2-7B-32K-Instruct": 6738415616,
+        "togethercomputer/CodeLlama-7b": 6738546688,
+        "togethercomputer/CodeLlama-7b-Python": 6738546688,
+        "togethercomputer/CodeLlama-7b-Instruct": 6738546688,
+        "togethercomputer/CodeLlama-13b": 13016028160,
+        "togethercomputer/CodeLlama-13b-Python": 13016028160,
+        "togethercomputer/CodeLlama-13b-Instruct": 13016028160,
+    }
+    try:
+        return pcount[name]
+    except Exception:
+        return 0
+
+
 class Finetune:
     def __init__(
         self,
@@ -23,7 +52,7 @@ def create(
         self,
         training_file: str,  # training file_id
         # validation_file: Optional[str] = None,  # validation file_id
-        model: Optional[str] = None,
+        model: str,
         n_epochs: int = 1,
         n_checkpoints: Optional[int] = 1,
         batch_size: Optional[int] = 32,
@@ -37,7 +66,7 @@ def create(
         suffix: Optional[
             str
         ] = None,  # resulting finetuned model name will include the suffix
-        # wandb_api_key: Optional[str] = None,
+        estimate_price: bool = False,
     ) -> Dict[Any, Any]:
         if n_epochs is None or n_epochs < 1:
             logger.fatal("The number of epochs must be specified")
@@ -94,6 +123,37 @@ def create(
             logger.critical(training_file_feedback)
             raise together.FileTypeError(training_file_feedback)
 
+        if estimate_price:
+            param_size = model_param_count(model)
+            if param_size == 0:
+                error = f"Unknown model {model}.  Cannot estimate price.  Please check the name of the model"
+                raise together.FileTypeError(error)
+
+            for file in uploaded_files["data"]:
+                if file["id"] == parameter_payload["training_file"]:
+                    ## This is the file
+                    byte_count = file["bytes"]
+                    token_estimate = int(int(file["bytes"]) / 4)
+                    data = {
+                        "method": "together_getPrice",
+                        "params": [
+                            model,
+                            "FT",
+                            {
+                                "tokens": token_estimate,
+                                "epochs": n_epochs,
+                                "parameters": model_param_count(model),
+                            },
+                        ],
+                        "id": 1,
+                    }
+                    r = requests.post("https://computer.together.xyz/", json=data)
+                    estimate = r.json()["result"]["total"]
+                    estimate /= 1000000000
+                    training_file_feedback = f"A rough price estimate for this job is ${estimate:.2f} USD. The estimated number of tokens is {token_estimate} tokens. Accurate pricing is not available until full tokenization has been performed. The actual price might be higher or lower depending on how the data is tokenized. Our token estimate is based on the number of bytes in the training file, {byte_count} bytes, divided by an average token length of 4 bytes. We currently have a per job minimum of $5.00 USD."
+                    print(training_file_feedback)
+                    exit()
+
         # Send POST request to SUBMIT FINETUNE JOB
         # HTTP headers for authorization
         headers = {