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[Model] Update multi-modal processor to support Mantis(LLaVA) model #10711

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merged 24 commits into from
Dec 7, 2024
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7b6c4f1
Add `get_dummy_data` to `MultiModalProcessor`; fix and test `iter_pla…
DarkLight1337 Nov 26, 2024
de8332a
Use merged processor for llava model
DarkLight1337 Nov 26, 2024
8b6804e
format
DarkLight1337 Nov 26, 2024
26e3fdf
Fix typo
DarkLight1337 Nov 26, 2024
93d27bc
Enable the test to pass on V1
DarkLight1337 Nov 26, 2024
d697241
Handle embedding inputs
DarkLight1337 Nov 26, 2024
ca11cc9
format
DarkLight1337 Nov 26, 2024
c32cba9
Merge branch 'main' into llava-mm-processor
DarkLight1337 Nov 27, 2024
6c5c9ca
Fix wrong ndim
DarkLight1337 Nov 27, 2024
0194324
Factor out `merge_placeholders`
DarkLight1337 Nov 27, 2024
09618d0
Fix placeholder maps handling on V0
DarkLight1337 Nov 27, 2024
5501458
Remove unused dummy data code
DarkLight1337 Nov 27, 2024
f3673c7
Update dummy model
DarkLight1337 Nov 27, 2024
37bc008
Enable overriding hf processor and tokenizer; fix `_apply_prompt_repl…
DarkLight1337 Nov 27, 2024
4805a9e
Improve error handling in `_resolve_matches`; merge matches directly
DarkLight1337 Nov 27, 2024
8539008
Avoid hashing
DarkLight1337 Nov 27, 2024
1e82a4a
Support and test Mantis model
DarkLight1337 Nov 27, 2024
cfbece4
Update docs
DarkLight1337 Nov 27, 2024
af68652
Merge branch 'main' into mantis
DarkLight1337 Nov 29, 2024
69aa12d
Merge branch 'main' into mantis
DarkLight1337 Dec 7, 2024
70c87d1
Fix type error
DarkLight1337 Dec 7, 2024
27b276b
Fix redundant code
DarkLight1337 Dec 7, 2024
c10c1cc
Remove convenience function as it makes things more complicated
DarkLight1337 Dec 7, 2024
d77cadd
Fix commands
DarkLight1337 Dec 7, 2024
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Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>
  • Loading branch information
DarkLight1337 committed Nov 26, 2024
commit ca11cc944d8b78181812cd180ee343b10139550a
2 changes: 1 addition & 1 deletion vllm/multimodal/processing.py
Original file line number Diff line number Diff line change
Expand Up @@ -582,7 +582,7 @@ def _apply_hf_processor(
mm_processor_kwargs: Mapping[str, object],
) -> BatchFeature:
hf_processor = self.ctx.get_hf_processor()

processor_data = dict[str, Any]()
passthrough_data = dict[str, Any]()
for k, v in mm_data.items():
Expand Down