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ollama-for-amd/model
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Jesse Gross 282bfaaa95 ollamarunner: Use a separate context per multimodal input 
Currently there is a single context per sequence, shared all by
all multimodal inputs. Since we build a vision encoder graph per
image, with a large number of inputs we can eventually hit the
maximum number of graph nodes per context.

This changes to use a separate context for each image, ensuring
that available resource limits are consistent.
2025-03-14 15:38:54 -07:00
..
imageproc
imageproc mllama refactor (#7537)
2024-12-14 19:50:15 -08:00
input
ml: Allow models to constrain inputs to a single batch
2025-03-14 15:38:54 -07:00
models
ollamarunner: Use a separate context per multimodal input
2025-03-14 15:38:54 -07:00
testdata
gemma2 impl
2025-03-11 14:35:08 -07:00
model_test.go
model: Update encoder cache to use multimodal input processing handler
2025-03-09 17:05:26 -07:00
model.go
ollamarunner: Use a separate context per multimodal input
2025-03-14 15:38:54 -07:00
process_text_spm_test.go
model: add more spm tokenizer tests
2025-03-11 14:49:20 -07:00
process_text_spm.go
model: validate left and right pairs before merging them
2025-03-11 14:49:20 -07:00
process_text_test.go
model: Don't unconditionally add special tokens
2025-03-06 16:54:16 -08:00
process_text.go
set non-causal attention
2025-03-11 14:49:18 -07:00