From 2571652305725dece8621e76dfc1cb09c447bf7c Mon Sep 17 00:00:00 2001 From: Shubham Toshniwal Date: Mon, 29 Sep 2025 15:29:26 -0700 Subject: [PATCH 01/11] Generation stat fixing Signed-off-by: Shubham Toshniwal --- nemo_skills/inference/generate.py | 34 +++++++++++++++---------------- nemo_skills/prompt/utils.py | 13 +++++++++++- 2 files changed, 28 insertions(+), 19 deletions(-) diff --git a/nemo_skills/inference/generate.py b/nemo_skills/inference/generate.py index 4361d394ca..be8e5b9c54 100644 --- a/nemo_skills/inference/generate.py +++ b/nemo_skills/inference/generate.py @@ -472,21 +472,10 @@ def dump_outputs(self, outputs, data_points, fout): output[self.cfg.generation_key] = output.pop("generation") # calculating total generation time - if self.cfg.add_generation_stats: - output["generation_end_time"] = time.time() - # TODO: start time is saved in data_point, not output, need to fix that - output["generation_time"] = ( - output["generation_end_time"] - original_data_point["generation_start_time"] - ) - else: - # generation_start_time was overriden, so restoring it from end and total - # TODO: this is a bit hacky, need a rewrite - if "generation_end_time" in original_data_point and "generation_time" in original_data_point: - output["generation_start_time"] = ( - original_data_point["generation_end_time"] - original_data_point["generation_time"] - ) - else: - output.pop("generation_start_time", None) + if not self.cfg.add_generation_stats: + output.pop("generation_start_time", None) + output.pop("generation_end_time", None) + output.pop("generation_time", None) output.pop("num_generated_tokens", None) for key in output: @@ -520,8 +509,20 @@ async def process_single_datapoint(self, data_point, all_data): if self.cfg.override_max_code_executions and self.cfg.total_code_executions_in_prompt is not None: generation_params["max_code_executions"] = data_point["total_code_executions"] + # Tracking the tokens and generation time + input_sequence_length = self.prompt.get_token_count(generation_params["prompt"]) + start_time = time.time() + result = await self.llm.generate_async(**generation_params) + end_time = time.time() + # Add the generation time and input sequence length + if self.cfg.add_generation_stats: + result["generation_start_time"] = start_time + result["generation_end_time"] = end_time + result["generation_time"] = end_time - start_time + + result["input_sequence_length"] = input_sequence_length return result async def apply_evaluation_hook(self, data_point): @@ -536,9 +537,6 @@ async def apply_evaluation_hook(self, data_point): async def _process_single_datapoint_with_semaphore(self, data_point, all_data, fout, pbar): """Process a single data point with semaphore control.""" async with self.semaphore: - # registering current time to calculate total generation time - data_point["generation_start_time"] = time.time() - # Generate output for this single data point output = await self.process_single_datapoint(data_point, all_data) # Apply evaluation hook if configured diff --git a/nemo_skills/prompt/utils.py b/nemo_skills/prompt/utils.py index ca89ddeec9..cc2a5dbe7a 100644 --- a/nemo_skills/prompt/utils.py +++ b/nemo_skills/prompt/utils.py @@ -18,7 +18,7 @@ import re from dataclasses import asdict, field from pathlib import Path -from typing import Any, Dict, List, Optional +from typing import Any, Dict, List, Optional, Union import yaml from transformers import AutoTokenizer @@ -302,6 +302,17 @@ def fill( return messages + def get_token_count(self, messages: Union[str, list[dict]]) -> int: + if self.tokenizer is None: + return None + + if isinstance(messages, str): + return len(self.tokenizer.encode(messages, add_special_tokens=False)) + elif isinstance(messages, list): + return len(self.tokenizer.apply_chat_template(messages, tokenize=True)) + else: + raise ValueError("messages must be a string or a list of dictionaries") + def __str__(self): return str(self.config) From b243231058c0b333bc4b6779367d2522a9160db5 Mon Sep 17 00:00:00 2001 From: Shubham Toshniwal Date: Mon, 29 Sep 2025 15:30:58 -0700 Subject: [PATCH 02/11] Generation stat fixing Signed-off-by: Shubham Toshniwal --- nemo_skills/prompt/utils.py | 14 +++++++++++++- 1 file changed, 13 insertions(+), 1 deletion(-) diff --git a/nemo_skills/prompt/utils.py b/nemo_skills/prompt/utils.py index cc2a5dbe7a..dd2960deea 100644 --- a/nemo_skills/prompt/utils.py +++ b/nemo_skills/prompt/utils.py @@ -303,13 +303,25 @@ def fill( return messages def get_token_count(self, messages: Union[str, list[dict]]) -> int: + """ + Count the number of tokens in a string or chat message list. + + Args: + messages (str | list[dict]): Input text or chat messages. + + Returns: + int | None: Token count, or None if no tokenizer is set. + """ if self.tokenizer is None: return None if isinstance(messages, str): return len(self.tokenizer.encode(messages, add_special_tokens=False)) elif isinstance(messages, list): - return len(self.tokenizer.apply_chat_template(messages, tokenize=True)) + try: + return len(self.tokenizer.apply_chat_template(messages, tokenize=True)) + except Exception as e: + raise ValueError(f"Invalid chat message format: {e}") else: raise ValueError("messages must be a string or a list of dictionaries") From 6cf7890e35b790f15953887508487f26f9ec4673 Mon Sep 17 00:00:00 2001 From: Shubham Toshniwal Date: Mon, 29 Sep 2025 15:32:10 -0700 Subject: [PATCH 03/11] Delete comment Signed-off-by: Shubham Toshniwal --- nemo_skills/inference/generate.py | 1 - 1 file changed, 1 deletion(-) diff --git a/nemo_skills/inference/generate.py b/nemo_skills/inference/generate.py index be8e5b9c54..ac58b7244e 100644 --- a/nemo_skills/inference/generate.py +++ b/nemo_skills/inference/generate.py @@ -471,7 +471,6 @@ def dump_outputs(self, outputs, data_points, fout): # all of the ground-truth data to the output file alongside the generated solutions output[self.cfg.generation_key] = output.pop("generation") - # calculating total generation time if not self.cfg.add_generation_stats: output.pop("generation_start_time", None) output.pop("generation_end_time", None) From 799239fcb6a7e677633f882d9da7ac8e3eeb9150 Mon Sep 17 00:00:00 2001 From: Shubham Toshniwal Date: Mon, 29 Sep 2025 16:07:38 -0700 Subject: [PATCH 04/11] Checking for empty prompt Signed-off-by: Shubham Toshniwal --- nemo_skills/inference/generate.py | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/nemo_skills/inference/generate.py b/nemo_skills/inference/generate.py index ac58b7244e..6421e22b49 100644 --- a/nemo_skills/inference/generate.py +++ b/nemo_skills/inference/generate.py @@ -509,7 +509,12 @@ async def process_single_datapoint(self, data_point, all_data): generation_params["max_code_executions"] = data_point["total_code_executions"] # Tracking the tokens and generation time - input_sequence_length = self.prompt.get_token_count(generation_params["prompt"]) + input_sequence_length = None + if self.prompt is not None: + if generation_params["prompt"] is not None: + input_sequence_length = self.prompt.get_token_count(generation_params["prompt"]) + + # Start to track the generation time start_time = time.time() result = await self.llm.generate_async(**generation_params) From 922cdb01d710d2451361dd3525728389195968a8 Mon Sep 17 00:00:00 2001 From: Shubham Toshniwal Date: Mon, 29 Sep 2025 19:08:54 -0400 Subject: [PATCH 05/11] Update nemo_skills/prompt/utils.py Co-authored-by: Igor Gitman Signed-off-by: Shubham Toshniwal --- nemo_skills/prompt/utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nemo_skills/prompt/utils.py b/nemo_skills/prompt/utils.py index dd2960deea..c6acfe4090 100644 --- a/nemo_skills/prompt/utils.py +++ b/nemo_skills/prompt/utils.py @@ -319,7 +319,7 @@ def get_token_count(self, messages: Union[str, list[dict]]) -> int: return len(self.tokenizer.encode(messages, add_special_tokens=False)) elif isinstance(messages, list): try: - return len(self.tokenizer.apply_chat_template(messages, tokenize=True)) + return len(self.tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True)) except Exception as e: raise ValueError(f"Invalid chat message format: {e}") else: From 8a6446cc678896fa6444797fbd223509adf0a6fa Mon Sep 17 00:00:00 2001 From: Shubham Toshniwal Date: Mon, 29 Sep 2025 16:09:44 -0700 Subject: [PATCH 06/11] Addressing the comments Signed-off-by: Shubham Toshniwal --- nemo_skills/inference/generate.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/nemo_skills/inference/generate.py b/nemo_skills/inference/generate.py index 6421e22b49..ba1dbe67cd 100644 --- a/nemo_skills/inference/generate.py +++ b/nemo_skills/inference/generate.py @@ -476,6 +476,7 @@ def dump_outputs(self, outputs, data_points, fout): output.pop("generation_end_time", None) output.pop("generation_time", None) output.pop("num_generated_tokens", None) + output.pop("input_sequence_length", None) for key in output: original_data_point.pop(key, None) @@ -526,7 +527,8 @@ async def process_single_datapoint(self, data_point, all_data): result["generation_end_time"] = end_time result["generation_time"] = end_time - start_time - result["input_sequence_length"] = input_sequence_length + if input_sequence_length is not None: + result["input_sequence_length"] = input_sequence_length return result async def apply_evaluation_hook(self, data_point): From bc6c18a385357c1e2ba8f82a06ceb5aa1180c953 Mon Sep 17 00:00:00 2001 From: Shubham Toshniwal Date: Mon, 29 Sep 2025 16:32:49 -0700 Subject: [PATCH 07/11] Addressing the comments Signed-off-by: Shubham Toshniwal --- nemo_skills/inference/generate.py | 40 +++++++++++++++------------ nemo_skills/prompt/utils.py | 46 +++++++++++++++++-------------- 2 files changed, 48 insertions(+), 38 deletions(-) diff --git a/nemo_skills/inference/generate.py b/nemo_skills/inference/generate.py index ba1dbe67cd..2efe38fa15 100644 --- a/nemo_skills/inference/generate.py +++ b/nemo_skills/inference/generate.py @@ -29,6 +29,7 @@ import litellm from omegaconf import ListConfig from tqdm import tqdm +from transformers import AutoTokenizer from nemo_skills.code_execution.sandbox import get_sandbox, sandbox_params from nemo_skills.inference.model import ( @@ -39,7 +40,7 @@ get_tool_calling_model, server_params, ) -from nemo_skills.prompt.utils import get_prompt +from nemo_skills.prompt.utils import get_prompt, get_token_count from nemo_skills.utils import ( chunk_data, get_help_message, @@ -271,8 +272,14 @@ def __init__(self, cfg: GenerateSolutionsConfig): if self.cfg.use_completions_api or self.cfg.server.get("enable_soft_fail", False): # These are the only cases where we need a tokenizer self.tokenizer = self.cfg.tokenizer or self.cfg.server["model"] + try: + self.hf_tokenizer = AutoTokenizer.from_pretrained(self.tokenizer) + except ValueError: + self.hf_tokenizer = None + LOG.warning("Not a valid huggingface tokenizer: %s", self.tokenizer) else: self.tokenizer = None + self.hf_tokenizer = None # Setup litellm cache self.setup_litellm_cache() @@ -321,8 +328,9 @@ def __init__(self, cfg: GenerateSolutionsConfig): self.output_lock = None def setup_prompt(self): + prompt = None if self.cfg.prompt_format == "openai": - return None + prompt = None prompt = get_prompt( prompt_config=self.cfg.prompt_config, @@ -331,6 +339,7 @@ def setup_prompt(self): examples_type=self.cfg.examples_type, system_message=self.cfg.system_message, ) + LOG.info("Prompt used: %s", prompt) return prompt @@ -509,23 +518,12 @@ async def process_single_datapoint(self, data_point, all_data): if self.cfg.override_max_code_executions and self.cfg.total_code_executions_in_prompt is not None: generation_params["max_code_executions"] = data_point["total_code_executions"] - # Tracking the tokens and generation time - input_sequence_length = None - if self.prompt is not None: - if generation_params["prompt"] is not None: - input_sequence_length = self.prompt.get_token_count(generation_params["prompt"]) - - # Start to track the generation time - start_time = time.time() - result = await self.llm.generate_async(**generation_params) - end_time = time.time() - # Add the generation time and input sequence length - if self.cfg.add_generation_stats: - result["generation_start_time"] = start_time - result["generation_end_time"] = end_time - result["generation_time"] = end_time - start_time + if self.prompt is not None: + input_sequence_length = get_token_count(self.prompt.tokenizer, generation_params["prompt"]) + elif self.hf_tokenizer is not None: + input_sequence_length = get_token_count(self.hf_tokenizer, generation_params["prompt"]) if input_sequence_length is not None: result["input_sequence_length"] = input_sequence_length @@ -544,7 +542,15 @@ async def _process_single_datapoint_with_semaphore(self, data_point, all_data, f """Process a single data point with semaphore control.""" async with self.semaphore: # Generate output for this single data point + start_time = time.time() output = await self.process_single_datapoint(data_point, all_data) + end_time = time.time() + + if self.cfg.add_generation_stats: + output["generation_start_time"] = start_time + output["generation_end_time"] = end_time + output["generation_time"] = end_time - start_time + # Apply evaluation hook if configured # TODO: note that this currently only evaluates independently--if there # is any post-processing that needs to be done on the full set of diff --git a/nemo_skills/prompt/utils.py b/nemo_skills/prompt/utils.py index c6acfe4090..6c7bb955d9 100644 --- a/nemo_skills/prompt/utils.py +++ b/nemo_skills/prompt/utils.py @@ -302,31 +302,35 @@ def fill( return messages - def get_token_count(self, messages: Union[str, list[dict]]) -> int: - """ - Count the number of tokens in a string or chat message list. + def __str__(self): + return str(self.config) - Args: - messages (str | list[dict]): Input text or chat messages. - Returns: - int | None: Token count, or None if no tokenizer is set. - """ - if self.tokenizer is None: - return None +def get_token_count(tokenizer, messages: Union[str, list[dict]]) -> int | None: + """ + Count the number of tokens in a string or chat message list. - if isinstance(messages, str): - return len(self.tokenizer.encode(messages, add_special_tokens=False)) - elif isinstance(messages, list): - try: - return len(self.tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True)) - except Exception as e: - raise ValueError(f"Invalid chat message format: {e}") - else: - raise ValueError("messages must be a string or a list of dictionaries") + Args: + messages (str | list[dict]): Input text or chat messages. - def __str__(self): - return str(self.config) + Returns: + int | None: Token count, or None if no tokenizer is set. + """ + if tokenizer is None: + return None + + if messages is None: + return None + + if isinstance(messages, str): + return len(tokenizer.encode(messages, add_special_tokens=False)) + elif isinstance(messages, list): + try: + return len(tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True)) + except Exception as e: + raise ValueError(f"Invalid chat message format: {e}") + else: + raise ValueError("messages must be a string or a list of dictionaries") def get_config_path(config: str, config_dir: str | None = None, config_extension: str = "yaml") -> Path: From cbf482f55148f1ed694e6888d802210fb855cf01 Mon Sep 17 00:00:00 2001 From: Shubham Toshniwal Date: Mon, 29 Sep 2025 17:00:14 -0700 Subject: [PATCH 08/11] Addressing the comments Signed-off-by: Shubham Toshniwal --- nemo_skills/inference/generate.py | 40 ++++++++++++++++++------------- 1 file changed, 24 insertions(+), 16 deletions(-) diff --git a/nemo_skills/inference/generate.py b/nemo_skills/inference/generate.py index f471282b14..c3963edb8b 100644 --- a/nemo_skills/inference/generate.py +++ b/nemo_skills/inference/generate.py @@ -114,6 +114,9 @@ class GenerateSolutionsConfig: # Useful when running judge jobs to keep the original generation statistics add_generation_stats: bool = True + # Count the number of tokens in the prompt + count_prompt_tokens: bool = False + generation_key: str = "generation" async_position_key: str = "_async_position" # key to use for preserving position in async loop in data dict @@ -196,7 +199,7 @@ def _post_init_validate_server(self): "Megatron server doesn't support chat completions and we can't infer tokenizer from model name. " "Please provide it with an explicit `tokenizer` parameter." ) - self.use_completions_api = True + self.cfg.use_completions_api = True LOG.warning("Megatron inference is extremely slow. It's highly recommended to use other server types!") def _post_init_validate_params(self): @@ -269,17 +272,15 @@ def __init__(self, cfg: GenerateSolutionsConfig): self.cfg.chat_template_kwargs = None # Setup tokenizer - if self.cfg.use_completions_api or self.cfg.server.get("enable_soft_fail", False): + if ( + self.cfg.use_completions_api + or self.cfg.server.get("enable_soft_fail", False) + or self.cfg.count_prompt_tokens + ): # These are the only cases where we need a tokenizer self.tokenizer = self.cfg.tokenizer or self.cfg.server["model"] - try: - self.hf_tokenizer = AutoTokenizer.from_pretrained(self.tokenizer) - except ValueError: - self.hf_tokenizer = None - LOG.warning("Not a valid huggingface tokenizer: %s", self.tokenizer) else: self.tokenizer = None - self.hf_tokenizer = None # Setup litellm cache self.setup_litellm_cache() @@ -291,6 +292,17 @@ def __init__(self, cfg: GenerateSolutionsConfig): self.prompt = self.setup_prompt() self.llm = self.setup_llm() + # Setup hf_tokenizer for counting prompt tokens + self.hf_tokenizer = None + if self.cfg.count_prompt_tokens: + if self.prompt is not None: + self.hf_tokenizer = self.prompt.tokenizer + else: + self.hf_tokenizer = AutoTokenizer.from_pretrained(self.tokenizer) + + if self.hf_tokenizer is None: + raise ValueError("Tokenizer could not be initialized. Needed for counting prompt tokens.") + if self.cfg.code_execution: self.extra_generate_params = self.prompt.get_code_execution_args() else: @@ -328,9 +340,8 @@ def __init__(self, cfg: GenerateSolutionsConfig): self.output_lock = None def setup_prompt(self): - prompt = None if self.cfg.prompt_format == "openai": - prompt = None + return None prompt = get_prompt( prompt_config=self.cfg.prompt_config, @@ -520,13 +531,10 @@ async def process_single_datapoint(self, data_point, all_data): result = await self.llm.generate_async(**generation_params) - if self.prompt is not None: - input_sequence_length = get_token_count(self.prompt.tokenizer, generation_params["prompt"]) - elif self.hf_tokenizer is not None: + if self.cfg.count_prompt_tokens: input_sequence_length = get_token_count(self.hf_tokenizer, generation_params["prompt"]) - - if input_sequence_length is not None: - result["input_sequence_length"] = input_sequence_length + if input_sequence_length is not None: + result["input_sequence_length"] = input_sequence_length return result async def apply_evaluation_hook(self, data_point): From f3a61b6492171b044cb3de09becb35ed7448ceba Mon Sep 17 00:00:00 2001 From: Shubham Toshniwal Date: Mon, 29 Sep 2025 17:03:50 -0700 Subject: [PATCH 09/11] Removing unwanted change Signed-off-by: Shubham Toshniwal --- nemo_skills/inference/generate.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nemo_skills/inference/generate.py b/nemo_skills/inference/generate.py index c3963edb8b..a035d2037d 100644 --- a/nemo_skills/inference/generate.py +++ b/nemo_skills/inference/generate.py @@ -199,7 +199,7 @@ def _post_init_validate_server(self): "Megatron server doesn't support chat completions and we can't infer tokenizer from model name. " "Please provide it with an explicit `tokenizer` parameter." ) - self.cfg.use_completions_api = True + self.use_completions_api = True LOG.warning("Megatron inference is extremely slow. It's highly recommended to use other server types!") def _post_init_validate_params(self): From 075f94f11b986d268011443a9e72fbf539f85f54 Mon Sep 17 00:00:00 2001 From: Shubham Toshniwal Date: Mon, 29 Sep 2025 17:24:52 -0700 Subject: [PATCH 10/11] Generation test change + comment Signed-off-by: Shubham Toshniwal --- nemo_skills/inference/generate.py | 3 +-- tests/test_generation.py | 12 ++++++------ 2 files changed, 7 insertions(+), 8 deletions(-) diff --git a/nemo_skills/inference/generate.py b/nemo_skills/inference/generate.py index a035d2037d..957d93edfe 100644 --- a/nemo_skills/inference/generate.py +++ b/nemo_skills/inference/generate.py @@ -533,8 +533,7 @@ async def process_single_datapoint(self, data_point, all_data): if self.cfg.count_prompt_tokens: input_sequence_length = get_token_count(self.hf_tokenizer, generation_params["prompt"]) - if input_sequence_length is not None: - result["input_sequence_length"] = input_sequence_length + result["input_sequence_length"] = input_sequence_length return result async def apply_evaluation_hook(self, data_point): diff --git a/tests/test_generation.py b/tests/test_generation.py index bc1e0eba8d..56fc29aefd 100644 --- a/tests/test_generation.py +++ b/tests/test_generation.py @@ -26,7 +26,7 @@ def test_eval_gsm8k_api(tmp_path): cmd = ( f"ns eval " f" --server_type=openai " - f" --model=meta/llama-3.1-8b-instruct " + f" --model=nvidia/nvidia-nemotron-nano-9b-v2 " f" --server_address=https://integrate.api.nvidia.com/v1 " f" --benchmarks=gsm8k " f" --output_dir={tmp_path} " @@ -53,11 +53,11 @@ def test_eval_judge_api(tmp_path): cmd = ( f"ns eval " f" --server_type=openai " - f" --model=meta/llama-3.1-8b-instruct " + f" --model=nvidia/nvidia-nemotron-nano-9b-v2" f" --server_address=https://integrate.api.nvidia.com/v1 " f" --benchmarks=math-500 " f" --output_dir={tmp_path} " - f" --judge_model=meta/llama-3.1-8b-instruct " + f" --judge_model=nvidia/nvidia-nemotron-nano-9b-v2 " f" --judge_server_address=https://integrate.api.nvidia.com/v1 " f" --judge_server_type=openai " f" --judge_generation_type=math_judge " @@ -85,7 +85,7 @@ def test_fail_on_api_key_env_var(tmp_path): cmd = ( f"ns eval " f" --server_type=openai " - f" --model=meta/llama-3.1-8b-instruct " + f" --model=nvidia/nvidia-nemotron-nano-9b-v2 " f" --server_address=https://integrate.api.nvidia.com/v1 " f" --benchmarks=gsm8k " f" --output_dir={tmp_path} " @@ -106,7 +106,7 @@ def test_succeed_on_api_key_env_var(tmp_path): f"unset NVIDIA_API_KEY && " f"ns eval " f" --server_type=openai " - f" --model=meta/llama-3.1-8b-instruct " + f" --model=nvidia/nvidia-nemotron-nano-9b-v2 " f" --server_address=https://integrate.api.nvidia.com/v1 " f" --benchmarks=gsm8k " f" --output_dir={tmp_path} " @@ -135,7 +135,7 @@ def test_generate_openai_format(tmp_path, format): cmd = ( f"ns generate " f" --server_type=openai " - f" --model=meta/llama-3.1-8b-instruct " + f" --model=nvidia/nvidia-nemotron-nano-9b-v2 " f" --server_address=https://integrate.api.nvidia.com/v1 " f" --input_file=/nemo_run/code/tests/data/openai-input-{format}.test " f" --output_dir={tmp_path} " From 1fd3e73945fd9494fd49ff26ed99e8251fff74ed Mon Sep 17 00:00:00 2001 From: Igor Gitman Date: Mon, 29 Sep 2025 17:41:23 -0700 Subject: [PATCH 11/11] Update tests/test_generation.py Signed-off-by: Igor Gitman --- tests/test_generation.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/test_generation.py b/tests/test_generation.py index 56fc29aefd..0d0f42c586 100644 --- a/tests/test_generation.py +++ b/tests/test_generation.py @@ -53,7 +53,7 @@ def test_eval_judge_api(tmp_path): cmd = ( f"ns eval " f" --server_type=openai " - f" --model=nvidia/nvidia-nemotron-nano-9b-v2" + f" --model=nvidia/nvidia-nemotron-nano-9b-v2 " f" --server_address=https://integrate.api.nvidia.com/v1 " f" --benchmarks=math-500 " f" --output_dir={tmp_path} "