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aa23412989
* Create llava-survery-v2.py * Update convert-image-encoder-to-gguf.py * Update convert-image-encoder-to-gguf.py * Rename llava-survery-v2.py to llava-surgery-v2.py * Update convert-image-encoder-to-gguf.py will now search for projector * Update convert-image-encoder-to-gguf.py whoops * Update llava-surgery-v2.py * Clip: Bugfix for normalization (it did not loat the 3 std and mean values) Clip: bicubic resize function Clip: added save-to-bmp/pil for debugging and conversion from/to 32/8 images Clip: added normalization with FP16 precision simulation (image tensors match HF implementation, can be switched off, only used for llava-1.6) Clip: added newline tensor, mergetype kv, image-grid kv, new resize-pad function with resolution from gridpoints Clip: clip_image_preprocess now returns a float * vector instead of float, this way llava 1.5 and 1.6 is supported llava: added ggml cpu graph for embedding patching, added spatial_unpad preliminary support, added a lot of comments that need to be cleaned when all is final convert-image-encoder: fixed image-grid flattening * whitespace corrections * ws * Tensors are now properly permuted. Before the embeddings were inserted 1:1, now they are split into the 24x24 patches as in reference. * ws * added verbose_prompt support into cli added stopwords for llava-1.6 into cli * moved llava functions to llava.cpp, made clip.h C compatible API, replaced vector style functions with pointers, added a debug define to remove functions from compilation while not needed * ws * convert : skip unknown tensors (need for LLaVA) * llava : update readme * llava : fix compile warnings * llava : style * convert : add --skip-unknown CLI arg * server : remove clip structs * bugfix for non llava-1.6 It should now work with llava-1.5 as well * clip : minor code rearrange * llava : update readme a bit --------- Co-authored-by: John <cmt-nct@users.noreply.github.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> |
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.. | ||
baby-llama | ||
batched | ||
batched-bench | ||
batched.swift | ||
beam-search | ||
benchmark | ||
convert-llama2c-to-ggml | ||
embedding | ||
export-lora | ||
finetune | ||
gguf | ||
imatrix | ||
infill | ||
jeopardy | ||
llama-bench | ||
llama.android | ||
llama.swiftui | ||
llava | ||
lookahead | ||
lookup | ||
main | ||
main-cmake-pkg | ||
parallel | ||
passkey | ||
perplexity | ||
quantize | ||
quantize-stats | ||
save-load-state | ||
server | ||
simple | ||
speculative | ||
sycl | ||
tokenize | ||
train-text-from-scratch | ||
alpaca.sh | ||
base-translate.sh | ||
chat-13B.bat | ||
chat-13B.sh | ||
chat-persistent.sh | ||
chat-vicuna.sh | ||
chat.sh | ||
CMakeLists.txt | ||
gpt4all.sh | ||
json-schema-to-grammar.py | ||
llama2-13b.sh | ||
llama2.sh | ||
llama.vim | ||
llm.vim | ||
make-ggml.py | ||
Miku.sh | ||
pydantic_models_to_grammar.py | ||
pydantic-models-to-grammar-examples.py | ||
reason-act.sh | ||
server-llama2-13B.sh |