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Add support for Chameleon #8543
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I have uploaded GGUFs to test this PR with here. |
mofosyne
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Review Complexity : Medium
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Jul 19, 2024
compilade
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Co-authored-by: compilade <[email protected]>
Co-authored-by: compilade <[email protected]>
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Co-Authored-By: nopperl <[email protected]>
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Co-Authored-By: nopperl <[email protected]>
will this ever get added :( |
I think it would still be a good addition. I've resolved all conflicts with master now, so it should be ready to merge. |
ggerganov
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Sep 28, 2024
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Thank you @nopperl looks like it got merged! |
matiaslin
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* convert chameleon hf to gguf * add chameleon tokenizer tests * fix lint * implement chameleon graph * add swin norm param * return qk norm weights and biases to original format * implement swin norm * suppress image token output * rem tabs * add comment to conversion * fix ci * check for k norm separately * adapt to new lora implementation * fix layer input for swin norm * move swin_norm in gguf writer * add comment regarding special token regex in chameleon pre-tokenizer * Update src/llama.cpp Co-authored-by: compilade <[email protected]> * fix punctuation regex in chameleon pre-tokenizer (@compilade) Co-authored-by: compilade <[email protected]> * fix lint * trigger ci --------- Co-authored-by: compilade <[email protected]>
dsx1986
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* convert chameleon hf to gguf * add chameleon tokenizer tests * fix lint * implement chameleon graph * add swin norm param * return qk norm weights and biases to original format * implement swin norm * suppress image token output * rem tabs * add comment to conversion * fix ci * check for k norm separately * adapt to new lora implementation * fix layer input for swin norm * move swin_norm in gguf writer * add comment regarding special token regex in chameleon pre-tokenizer * Update src/llama.cpp Co-authored-by: compilade <[email protected]> * fix punctuation regex in chameleon pre-tokenizer (@compilade) Co-authored-by: compilade <[email protected]> * fix lint * trigger ci --------- Co-authored-by: compilade <[email protected]>
arthw
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* convert chameleon hf to gguf * add chameleon tokenizer tests * fix lint * implement chameleon graph * add swin norm param * return qk norm weights and biases to original format * implement swin norm * suppress image token output * rem tabs * add comment to conversion * fix ci * check for k norm separately * adapt to new lora implementation * fix layer input for swin norm * move swin_norm in gguf writer * add comment regarding special token regex in chameleon pre-tokenizer * Update src/llama.cpp Co-authored-by: compilade <[email protected]> * fix punctuation regex in chameleon pre-tokenizer (@compilade) Co-authored-by: compilade <[email protected]> * fix lint * trigger ci --------- Co-authored-by: compilade <[email protected]>
arthw
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Nov 18, 2024
* convert chameleon hf to gguf * add chameleon tokenizer tests * fix lint * implement chameleon graph * add swin norm param * return qk norm weights and biases to original format * implement swin norm * suppress image token output * rem tabs * add comment to conversion * fix ci * check for k norm separately * adapt to new lora implementation * fix layer input for swin norm * move swin_norm in gguf writer * add comment regarding special token regex in chameleon pre-tokenizer * Update src/llama.cpp Co-authored-by: compilade <[email protected]> * fix punctuation regex in chameleon pre-tokenizer (@compilade) Co-authored-by: compilade <[email protected]> * fix lint * trigger ci --------- Co-authored-by: compilade <[email protected]>
@nopperl any plans to tackle image->text and text->image? |
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python
python script changes
Review Complexity : Medium
Generally require more time to grok but manageable by beginner to medium expertise level
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This PR adds support for the Chameleon model. For now, this implementation only supports text->text inference and serves as base to implement the (more interesting) image->text, text->image and interleaved pipelines. However, such an implementation will probably require some changes to the CLI and internal architecture, so I suggest to do this in a separate PR.
Chameleon is based on the Llama-2 architecture with the following changes:
Note 1: in order to enable text->text inference, the image token logits are suppressed similar to the HF implementation. This needs to be removed when support for images is added.
Note 2: I implemented swin-norm, but I haven't tested it yet, as it is only used by Chameleon-30B.
To test it:
Output:
Reference (requires transformers>=4.43.0.dev0):
Reference output:
Partially addresses #7995.