Move convert.py to examples/convert-legacy-llama.py (#7430)
* Move convert.py to examples/convert-no-torch.py * Fix CI, scripts, readme files * convert-no-torch -> convert-legacy-llama * Move vocab thing to vocab.py * Fix convert-no-torch -> convert-legacy-llama * Fix lost convert.py in ci/run.sh * Fix imports * Fix gguf not imported correctly * Fix flake8 complaints * Fix check-requirements.sh * Get rid of ADDED_TOKENS_FILE, FAST_TOKENIZER_FILE * Review fixes
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@ -50,10 +50,10 @@ python ./examples/llava/llava-surgery.py -m ../llava-v1.5-7b
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python ./examples/llava/convert-image-encoder-to-gguf.py -m ../clip-vit-large-patch14-336 --llava-projector ../llava-v1.5-7b/llava.projector --output-dir ../llava-v1.5-7b
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```
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5. Use `convert.py` to convert the LLaMA part of LLaVA to GGUF:
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5. Use `examples/convert-legacy-llama.py` to convert the LLaMA part of LLaVA to GGUF:
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```sh
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python ./convert.py ../llava-v1.5-7b --skip-unknown
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python ./examples/convert-legacy-llama.py ../llava-v1.5-7b --skip-unknown
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```
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Now both the LLaMA part and the image encoder are in the `llava-v1.5-7b` directory.
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@ -92,7 +92,7 @@ python ./examples/llava/convert-image-encoder-to-gguf.py -m vit --llava-projecto
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6) Then convert the model to gguf format:
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```console
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python ./convert.py ../llava-v1.6-vicuna-7b/ --skip-unknown
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python ./examples/convert-legacy-llama.py ../llava-v1.6-vicuna-7b/ --skip-unknown
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```
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7) And finally we can run the llava-cli using the 1.6 model version:
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