misc fixes (#3085)
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@@ -67,9 +67,23 @@ mv ./outputs/gpt-oss-out/merged/* ./outputs/gpt-oss-out/
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### Inferencing your fine-tuned model
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### Inferencing your fine-tuned model
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#### vLLM
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GPT-OSS support in vLLM does not exist in a stable release yet. See https://x.com/MaziyarPanahi/status/1955741905515323425
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GPT-OSS support in vLLM does not exist in a stable release yet. See https://x.com/MaziyarPanahi/status/1955741905515323425
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for more information about using a special vllm-openai docker image for inferencing with vLLM.
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for more information about using a special vllm-openai docker image for inferencing with vLLM.
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Optionally, vLLM can be installed from nightly:
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```bash
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pip install --no-build-isolation --pre -U vllm --extra-index-url https://wheels.vllm.ai/nightly
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```
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and the vLLM server can be started with the following command (modify `--tensor-parallel-size 8` to match your environment):
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```bash
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vllm serve ./outputs/gpt-oss-out/ --served-model-name axolotl/gpt-oss-20b --host 0.0.0.0 --port 8888 --tensor-parallel-size 8
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```
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#### SGLang
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SGLang has 0-day support in main, see https://github.com/sgl-project/sglang/issues/8833 for infomation on installing
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SGLang has 0-day support in main, see https://github.com/sgl-project/sglang/issues/8833 for infomation on installing
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SGLang from source. Once you've installed SGLang, run the following command to launch a SGLang server:
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SGLang from source. Once you've installed SGLang, run the following command to launch a SGLang server:
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@@ -15,7 +15,7 @@ datasets:
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field_thinking: thinking
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field_thinking: thinking
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template_thinking_key: thinking
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template_thinking_key: thinking
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dataset_prepared_path: last_run_prepared
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dataset_prepared_path: ./outputs/last_run_prepared
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val_set_size: 0
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val_set_size: 0
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output_dir: ./outputs/gpt-oss-out/
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output_dir: ./outputs/gpt-oss-out/
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@@ -15,7 +15,7 @@ datasets:
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field_thinking: thinking
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field_thinking: thinking
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template_thinking_key: thinking
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template_thinking_key: thinking
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dataset_prepared_path: last_run_prepared
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dataset_prepared_path: ./outputs/last_run_prepared
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val_set_size: 0
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val_set_size: 0
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output_dir: ./outputs/gpt-oss-out/
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output_dir: ./outputs/gpt-oss-out/
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@@ -82,7 +82,7 @@ class ModalCloud(Cloud):
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return res
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return res
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def get_image(self):
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def get_image(self):
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docker_tag = "main-py3.11-cu124-2.6.0"
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docker_tag = "main-py3.11-cu126-2.7.1"
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if self.config.docker_tag:
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if self.config.docker_tag:
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docker_tag = self.config.docker_tag
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docker_tag = self.config.docker_tag
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docker_image = f"axolotlai/axolotl:{docker_tag}"
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docker_image = f"axolotlai/axolotl:{docker_tag}"
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@@ -64,7 +64,7 @@ def do_inference(
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importlib.import_module("axolotl.prompters"), prompter
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importlib.import_module("axolotl.prompters"), prompter
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)
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)
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elif cfg.chat_template:
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elif cfg.chat_template:
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chat_template_str = get_chat_template(cfg.chat_template)
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chat_template_str = get_chat_template(cfg.chat_template, tokenizer=tokenizer)
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elif cfg.datasets[0].type == "chat_template":
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elif cfg.datasets[0].type == "chat_template":
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chat_template_str = get_chat_template_from_config(
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chat_template_str = get_chat_template_from_config(
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cfg=cfg, ds_cfg=cfg.datasets[0], tokenizer=tokenizer
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cfg=cfg, ds_cfg=cfg.datasets[0], tokenizer=tokenizer
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@@ -97,7 +97,8 @@ def do_cli(
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"""
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"""
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# pylint: disable=duplicate-code
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# pylint: disable=duplicate-code
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os.environ["AXOLOTL_IS_PREPROCESS"] = "1"
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os.environ["AXOLOTL_IS_PREPROCESS"] = "1"
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parsed_cfg = load_cfg(config, **kwargs)
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is_preprocess = kwargs.pop("is_preprocess", True)
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parsed_cfg = load_cfg(config, is_preprocess=is_preprocess, **kwargs)
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parsed_cfg.is_preprocess = True
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parsed_cfg.is_preprocess = True
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parser = transformers.HfArgumentParser(PreprocessCliArgs)
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parser = transformers.HfArgumentParser(PreprocessCliArgs)
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parsed_cli_args, _ = parser.parse_args_into_dataclasses(
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parsed_cli_args, _ = parser.parse_args_into_dataclasses(
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