[Tests]: Adding dummy causal models for testing in regular CI run #427
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Signed-off-by: Abukhoyer Shaik <abukhoye@qti.qualcomm.com>
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Signed-off-by: Abukhoyer Shaik <abukhoye@qti.qualcomm.com>
Signed-off-by: Abukhoyer Shaik <abukhoye@qti.qualcomm.com>
Signed-off-by: Abukhoyer Shaik <abukhoye@qti.qualcomm.com>
Signed-off-by: Abukhoyer Shaik <abukhoye@qti.qualcomm.com>
Signed-off-by: Abukhoyer Shaik <abukhoye@qti.qualcomm.com>
Signed-off-by: Abukhoyer Shaik <abukhoye@qti.qualcomm.com>
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Purpose of this PR:
This update aims to reduce test execution time for causal language model inference. Previously, tests were run using full-scale models with one or two layers, which was inefficient and time-consuming.
What’s Changed:
Introduced dummy models with significantly smaller configurations by adjusting parameters such as
max_position_embeddings, num_hidden_layers, num_attention_heads, hidden_size, intermediate_size, vocab_size and additional_params.These lightweight models are used exclusively for testing purposes to ensure faster execution without compromising test coverage.
Note: This optimization is applied only to causal language models.