* fix(gguf-py): special tokens are no longer skipped when add_<token>_token is set to false
* fix(gguf-py): added missing cls and mask token ids to the gguf metadata
* Fix memory management in llava and server code
Fixes this error:
llama_new_context_with_model: graph splits (measure): 3
Available slots:
-> Slot 0 - max context: 6000
{"timestamp":1707926446,"level":"INFO","function":"main","line":2623,"message":"model loaded"}
all slots are idle and system prompt is empty, clear the KV cache
slot 0 - loaded image
slot 0 is processing [task id: 0]
slot 0 : kv cache rm - [0, end)
slot 0 - encoding image [id: 1]
munmap_chunk(): invalid pointer
Aborted
* Make it cleaner by checking size in batch free wrapper
* 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>
* Early return for zero size calls to get_tensor.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
* Update ggml-kompute.cpp
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Update ggml-kompute.cpp
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Add an early return to the get/set tensor when the size is null.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
* Early return after the assertions.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
* Since we do the early return in the generic backend now no reason to do so here as well.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
---------
Signed-off-by: Adam Treat <treat.adam@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* finetune: rename feed-forward tensors (w1/w2/w3)
This commit renames the feed-forward tensors w1, w2 and w3 to ffn_gate,
ffn_down and ffn_up respectively.
The motivation for this change is to make it easier to understand the
purpose of the tensors. This also seems to be inline with the names
used in the llama_layer struct in llama.cpp.
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* train-text-from-scratch: rename ff tensors
This commit renames the feed-forward tensors w1, w2 and w3 to ffn_gate,
ffn_down and ffn_up respectively.
The motivation for this change is to make it easier to understand the
purpose of the tensors. This also seems to be inline with the names
used in the llama_layer struct in llama.cpp
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
---------
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* batched embedding: pool outputs by sequence id. updated embedding example
* bring back non-causal attention
* embd : minor improvements
* llama : minor
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* make: add error message for bad CUDA version
* Update Makefile
Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>
---------
Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>
* llava: remove prog parameter from ArgumentParser
This commit removes the `prog` parameter from `ArgumentParser`
so that it uses the default value which is the name of the script.
The motivation for this change is that currently the usage output looks
like this:
```console
$ python examples/llava/convert-image-encoder-to-gguf.py --help
usage: convert_hf_to_gguf.py [-h] ...
```
And with this change it will look like this:
```console
$ python examples/llava/convert-image-encoder-to-gguf.py --help
usage: convert-image-encoder-to-gguf.py [-h] ...
```
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* ci: add W503 to flake8 ignore list
This commit adds W503 to the ignore list for flake8. This is done to
avoid the following error:
W503 line break before binary operator
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
---------
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* BERT model graph construction (build_bert)
* WordPiece tokenizer (llm_tokenize_wpm)
* Add flag for non-causal attention models
* Allow for models that only output embeddings
* Support conversion of BERT models to GGUF
* Based on prior work by @xyzhang626 and @skeskinen
---------
Co-authored-by: Jared Van Bortel <jared@nomic.ai>
Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
