Llama3.1 with torchtune #1123
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Llama3.1 with torchtune #1123
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/torchchat/1123
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 1599c2b with merge base 964d437 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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This PR makes torchchat support multi-modality model definition and constructions. To show our power in multi-modality area, we integrate flamingo component into our system. Note that this is only for bare-minimum support for model definition. Please check openai_api_multimodal branch for e2e, and #1123 (comment) for better structure and llama3.1 support
Jack-Khuu
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Sep 11, 2024
torchchat/cli/builder.py
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| @@ -35,6 +35,14 @@ | |||
| from torchchat.utils.measure_time import measure_time | |||
| from torchchat.utils.quantize import quantize_model | |||
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| # bypass the import issue before torchao is ready on macos | |||
| try: | |||
| from torchtune.training import set_default_dtype | |||
| @@ -11,6 +11,7 @@ | |||
| from enum import Enum | |||
| from pathlib import Path | |||
| from typing import Callable, Dict, Optional, Union | |||
| from abc import ABC, abstractmethod | |||
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should be one of the Model's parents. Fixed it.
torchchat/model.py
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| if isinstance(self.config.transformer_args[name], dict): | ||
| modules[name] = module_class(**self.config.transformer_args[name]) | ||
| else: | ||
| modules[name] = module_class(self.config.transformer_args[name]) |
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| if isinstance(self.config.transformer_args[name], dict): | |
| modules[name] = module_class(**self.config.transformer_args[name]) | |
| else: | |
| modules[name] = module_class(self.config.transformer_args[name]) | |
| if isinstance(config_args := self.config.transformer_args[name], dict): | |
| modules[name] = module_class(**config_args) | |
| else: | |
| modules[name] = module_class(config_args) |
torchchat/model.py
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| class FlamingoModel(Model): | ||
| def forward(self, tokens: Tensor, encoder_input: Optional[Dict[str, Tensor]] = None, encoder_mask: Optional[Tensor] = None) -> Tensor: |
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This PR aims to add torchtune llama3.1 support while keep the original torchchat llama3.1 for reference.
To play with it:
The command for original model should be the same:
If you want to play with torchtune 3.1 model, consider using: