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Fix converter (NVIDIA#8960)
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Signed-off-by: yaoyu-33 <[email protected]>
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yaoyu-33 authored and galv committed Apr 29, 2024
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If converting from Hugging Face, set the version to `huggingface` and the architecture (`arch`) to the Hugging Face model name (e.g., `yuvalkirstain/PickScore_v1`).
Additionally, provide a NeMo hparams file with the correct model architecture arguments. Refer to examples/multimodal/foundation/clip/conf/megatron_clip_config.yaml.
After conversion, you can verify with the following command:
wget https://upload.wikimedia.org/wikipedia/commons/0/0f/1665_Girl_with_a_Pearl_Earring.jpg
python /opt/NeMo/examples/multimodal/vision_language_foundation/clip/megatron_clip_infer.py \
model.restore_from_path=./open_clip.nemo \
image_path=./1665_Girl_with_a_Pearl_Earring.jpg \
texts='["a dog", "a boy", "a girl"]'
It should generate a high probability for "a girl" tag, e.g.
Given image's CLIP text probability: [('a dog', 0.0049710185), ('a boy', 0.002258187), ('a girl', 0.99277073)]
"""

import os
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".pre_layrnorm.bias": ".preprocess_layernorm.bias",
".post_layernorm.weight": ".transformer.final_layernorm.weight",
".post_layernorm.bias": ".transformer.final_layernorm.bias",
".backbone.embeddings.position_embedding.weight": ".backbone.position_embeddings.weight",
".language_model.embeddings.position_embedding.weight": ".language_model.embedding.position_embeddings.weight",
".backbone.embeddings.position_embedding.weight": ".backbone.position_embeddings",
".language_model.embeddings.position_embedding.weight": ".language_model.embedding.position_embeddings",
".embeddings.class_embedding": ".cls_token",
".backbone.embeddings.patch_embedding.weight": ".backbone.conv1.weight",
".final_layer_norm.weight": ".encoder.final_layernorm.weight",
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