llava : Add Granite Vision Support (#11794)
* Add super wip scripts for multimodal granite gguf Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Add example for converting mmgranite to gguf Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * remove hardcoded path Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Add vision feature layer to gguf params Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Clean up llava surgery and remove name substitution hacks Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Add transformers llava next tensor name mapping Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Make siglip / openclip mutuall exclusive Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Fix projector linear substitution Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Fix linear 2 substitution index Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Increase max flattened gridpoints to 64 Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Fix hardcoded concat for multiple feature layers Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Pull vision feature layers out of gguf keys Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * fix num gridpoints and use all layers Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Avoid dropping last image encoder layer in llava models Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Use 10 for max number of patches Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Standardize vision feature layers Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Cleanup logs Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Update comment for vision feature layer init Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Update notes for alternative to legacy llm conversion script Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Fix notes rendering Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Add v prefix to vision feature layer log Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Use current defaults for feature layer Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Use constant for max gridpoints / feat layers, style fixes Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * clarify non-negative feature layers Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Remove CLIP_API from func signature Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * USE MAX_IMAGE_FEATURE_LAYERS const in layer calc Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Clarify feature layers are non negative ints and not uint Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Fix condition for reading feature layers Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * pop last llava layer when feature layers are unset Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Fix unset vision layer 0 Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Update examples/llava/clip.cpp Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com> * Reenable assertion for out of bounds get_rows Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Use std vector for gridpoints and feature layers Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Caculate max feature layer at load time Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Include base patch for granite vision allocation Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Fix trailing whitespace Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Add max num patches = 10 back for minicpmv Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Use unordered set to store feature layers Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com> Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Use max feature layer for postnorm Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Apply suggestions from code review --------- Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com>
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@ -101,8 +101,27 @@ python ./examples/convert_legacy_llama.py ../llava-v1.6-vicuna-7b/ --skip-unknow
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```
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**note** llava-1.6 needs more context than llava-1.5, at least 3000 is needed (just run it at -c 4096)
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**note** llava-1.6 greatly benefits from batched prompt processing (defaults work)
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**note** if the language model in step `6)` is incompatible with the legacy conversion script, the easiest way handle the LLM model conversion is to load the model in transformers, and export only the LLM from the llava next model.
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```python
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import os
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import transformers
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model_path = ...
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llm_export_path = ...
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tokenizer = transformers.AutoTokenizer.from_pretrained(model_path)
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model = transformers.AutoModelForImageTextToText.from_pretrained(model_path)
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tokenizer.save_pretrained(llm_export_path)
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model.language_model.save_pretrained(llm_export_path)
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```
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Then, you can convert the LLM using the `convert_hf_to_gguf.py` script, which handles more LLM architectures.
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## llava-cli templating and llava-1.6 prompting
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llava-1.5 models all use the same vicuna prompt, here you can just add your image question like `-p "Provide a full description."`
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