Add unit test verifying compatibility with huggingface models #1352
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…h#1352) Summary: Our current unit tests for LLM Attribution use mocked models which are similar to huggingface transformer models (e.g. Llama, Llama2), but may have some unexpected differences such as [this](https://discuss.pytorch.org/t/trying-to-explain-zephyr-generative-llm/195262/3?fbclid=IwZXh0bgNhZW0CMTEAAR3REGbJsdhbNqG5LAyQ9_2J-82nPmNjt5avVyvNw-l8SMTWVXfI2DqIE8w_aem_GRP8EzELKtqDXDMZmox3Uw). To validate coverage and ensure compatibility with future changes to models, we would like to add tests using huggingface models directly and validate compatibility with LLM Attribution, which will help us quickly catch any breaking changes. So far we only test for model type `LlamaForCausalLM` Differential Revision: D62894898
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…h#1352) Summary: Pull Request resolved: pytorch#1352 Our current unit tests for LLM Attribution use mocked models which are similar to huggingface transformer models (e.g. Llama, Llama2), but may have some unexpected differences such as [this](https://discuss.pytorch.org/t/trying-to-explain-zephyr-generative-llm/195262/3?fbclid=IwZXh0bgNhZW0CMTEAAR3REGbJsdhbNqG5LAyQ9_2J-82nPmNjt5avVyvNw-l8SMTWVXfI2DqIE8w_aem_GRP8EzELKtqDXDMZmox3Uw). To validate coverage and ensure compatibility with future changes to models, we would like to add tests using huggingface models directly and validate compatibility with LLM Attribution, which will help us quickly catch any breaking changes. So far we only test for model type `LlamaForCausalLM` Differential Revision: D62894898
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…h#1352) Summary: Pull Request resolved: pytorch#1352 Our current unit tests for LLM Attribution use mocked models which are similar to huggingface transformer models (e.g. Llama, Llama2), but may have some unexpected differences such as [this](https://discuss.pytorch.org/t/trying-to-explain-zephyr-generative-llm/195262/3?fbclid=IwZXh0bgNhZW0CMTEAAR3REGbJsdhbNqG5LAyQ9_2J-82nPmNjt5avVyvNw-l8SMTWVXfI2DqIE8w_aem_GRP8EzELKtqDXDMZmox3Uw). To validate coverage and ensure compatibility with future changes to models, we would like to add tests using huggingface models directly and validate compatibility with LLM Attribution, which will help us quickly catch any breaking changes. So far we only test for model type `LlamaForCausalLM` Differential Revision: D62894898
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…h#1352) Summary: Pull Request resolved: pytorch#1352 Our current unit tests for LLM Attribution use mocked models which are similar to huggingface transformer models (e.g. Llama, Llama2), but may have some unexpected differences such as [this](https://discuss.pytorch.org/t/trying-to-explain-zephyr-generative-llm/195262/3?fbclid=IwZXh0bgNhZW0CMTEAAR3REGbJsdhbNqG5LAyQ9_2J-82nPmNjt5avVyvNw-l8SMTWVXfI2DqIE8w_aem_GRP8EzELKtqDXDMZmox3Uw). To validate coverage and ensure compatibility with future changes to models, we would like to add tests using huggingface models directly and validate compatibility with LLM Attribution, which will help us quickly catch any breaking changes. So far we only test for model type `LlamaForCausalLM` Differential Revision: D62894898
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…h#1352) Summary: Pull Request resolved: pytorch#1352 Our current unit tests for LLM Attribution use mocked models which are similar to huggingface transformer models (e.g. Llama, Llama2), but may have some unexpected differences such as [this](https://discuss.pytorch.org/t/trying-to-explain-zephyr-generative-llm/195262/3?fbclid=IwZXh0bgNhZW0CMTEAAR3REGbJsdhbNqG5LAyQ9_2J-82nPmNjt5avVyvNw-l8SMTWVXfI2DqIE8w_aem_GRP8EzELKtqDXDMZmox3Uw). To validate coverage and ensure compatibility with future changes to models, we would like to add tests using huggingface models directly and validate compatibility with LLM Attribution, which will help us quickly catch any breaking changes. So far we only test for model type `LlamaForCausalLM` Differential Revision: D62894898
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…h#1352) Summary: Pull Request resolved: pytorch#1352 Our current unit tests for LLM Attribution use mocked models which are similar to huggingface transformer models (e.g. Llama, Llama2), but may have some unexpected differences such as [this](https://discuss.pytorch.org/t/trying-to-explain-zephyr-generative-llm/195262/3?fbclid=IwZXh0bgNhZW0CMTEAAR3REGbJsdhbNqG5LAyQ9_2J-82nPmNjt5avVyvNw-l8SMTWVXfI2DqIE8w_aem_GRP8EzELKtqDXDMZmox3Uw). To validate coverage and ensure compatibility with future changes to models, we would like to add tests using huggingface models directly and validate compatibility with LLM Attribution, which will help us quickly catch any breaking changes. So far we only test for model type `LlamaForCausalLM` Differential Revision: D62894898
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…h#1352) Summary: Pull Request resolved: pytorch#1352 Our current unit tests for LLM Attribution use mocked models which are similar to huggingface transformer models (e.g. Llama, Llama2), but may have some unexpected differences such as [this](https://discuss.pytorch.org/t/trying-to-explain-zephyr-generative-llm/195262/3?fbclid=IwZXh0bgNhZW0CMTEAAR3REGbJsdhbNqG5LAyQ9_2J-82nPmNjt5avVyvNw-l8SMTWVXfI2DqIE8w_aem_GRP8EzELKtqDXDMZmox3Uw). To validate coverage and ensure compatibility with future changes to models, we would like to add tests using huggingface models directly and validate compatibility with LLM Attribution, which will help us quickly catch any breaking changes. So far we only test for model type `LlamaForCausalLM` Differential Revision: D62894898
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…h#1352) Summary: Pull Request resolved: pytorch#1352 Our current unit tests for LLM Attribution use mocked models which are similar to huggingface transformer models (e.g. Llama, Llama2), but may have some unexpected differences such as [this](https://discuss.pytorch.org/t/trying-to-explain-zephyr-generative-llm/195262/3?fbclid=IwZXh0bgNhZW0CMTEAAR3REGbJsdhbNqG5LAyQ9_2J-82nPmNjt5avVyvNw-l8SMTWVXfI2DqIE8w_aem_GRP8EzELKtqDXDMZmox3Uw). To validate coverage and ensure compatibility with future changes to models, we would like to add tests using huggingface models directly and validate compatibility with LLM Attribution, which will help us quickly catch any breaking changes. So far we only test for model type `LlamaForCausalLM` Differential Revision: D62894898
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…h#1352) Summary: Pull Request resolved: pytorch#1352 Our current unit tests for LLM Attribution use mocked models which are similar to huggingface transformer models (e.g. Llama, Llama2), but may have some unexpected differences such as [this](https://discuss.pytorch.org/t/trying-to-explain-zephyr-generative-llm/195262/3?fbclid=IwZXh0bgNhZW0CMTEAAR3REGbJsdhbNqG5LAyQ9_2J-82nPmNjt5avVyvNw-l8SMTWVXfI2DqIE8w_aem_GRP8EzELKtqDXDMZmox3Uw). To validate coverage and ensure compatibility with future changes to models, we would like to add tests using huggingface models directly and validate compatibility with LLM Attribution, which will help us quickly catch any breaking changes. So far we only test for model type `LlamaForCausalLM` Differential Revision: D62894898
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…h#1352) Summary: Pull Request resolved: pytorch#1352 Our current unit tests for LLM Attribution use mocked models which are similar to huggingface transformer models (e.g. Llama, Llama2), but may have some unexpected differences such as [this](https://discuss.pytorch.org/t/trying-to-explain-zephyr-generative-llm/195262/3?fbclid=IwZXh0bgNhZW0CMTEAAR3REGbJsdhbNqG5LAyQ9_2J-82nPmNjt5avVyvNw-l8SMTWVXfI2DqIE8w_aem_GRP8EzELKtqDXDMZmox3Uw). To validate coverage and ensure compatibility with future changes to models, we would like to add tests using huggingface models directly and validate compatibility with LLM Attribution, which will help us quickly catch any breaking changes. So far we only test for model type `LlamaForCausalLM` Reviewed By: vivekmig Differential Revision: D62894898
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…h#1352) Summary: Pull Request resolved: pytorch#1352 Our current unit tests for LLM Attribution use mocked models which are similar to huggingface transformer models (e.g. Llama, Llama2), but may have some unexpected differences such as [this](https://discuss.pytorch.org/t/trying-to-explain-zephyr-generative-llm/195262/3?fbclid=IwZXh0bgNhZW0CMTEAAR3REGbJsdhbNqG5LAyQ9_2J-82nPmNjt5avVyvNw-l8SMTWVXfI2DqIE8w_aem_GRP8EzELKtqDXDMZmox3Uw). To validate coverage and ensure compatibility with future changes to models, we would like to add tests using huggingface models directly and validate compatibility with LLM Attribution, which will help us quickly catch any breaking changes. So far we only test for model type `LlamaForCausalLM` Reviewed By: vivekmig Differential Revision: D62894898
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…h#1352) Summary: Pull Request resolved: pytorch#1352 Our current unit tests for LLM Attribution use mocked models which are similar to huggingface transformer models (e.g. Llama, Llama2), but may have some unexpected differences such as [this](https://discuss.pytorch.org/t/trying-to-explain-zephyr-generative-llm/195262/3?fbclid=IwZXh0bgNhZW0CMTEAAR3REGbJsdhbNqG5LAyQ9_2J-82nPmNjt5avVyvNw-l8SMTWVXfI2DqIE8w_aem_GRP8EzELKtqDXDMZmox3Uw). To validate coverage and ensure compatibility with future changes to models, we would like to add tests using huggingface models directly and validate compatibility with LLM Attribution, which will help us quickly catch any breaking changes. So far we only test for model type `LlamaForCausalLM` Reviewed By: vivekmig Differential Revision: D62894898
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Summary:
Our current unit tests for LLM Attribution use mocked models which are similar to huggingface transformer models (e.g. Llama, Llama2), but may have some unexpected differences such as this. To validate coverage and ensure compatibility with future changes to models, we would like to add tests using huggingface models directly and validate compatibility with LLM Attribution, which will help us quickly catch any breaking changes.
So far we only test for model type
LlamaForCausalLMDifferential Revision: D62894898