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authorJohn <78893154+cmp-nct@users.noreply.github.com>2024-02-14 08:38:35 +0100
committerGitHub <noreply@github.com>2024-02-14 09:38:35 +0200
commitaa2341298924ac89778252015efcb792f2df1e20 (patch)
tree1b7702dd6cf16b25495b6acf87467106ab2b75e0 /examples/llava/README.md
parentf5ca054855dea83f424003162f26de376e5643f6 (diff)
llava : support v1.6 (#5267)
* 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>
Diffstat (limited to 'examples/llava/README.md')
-rw-r--r--examples/llava/README.md12
1 files changed, 9 insertions, 3 deletions
diff --git a/examples/llava/README.md b/examples/llava/README.md
index 19f1a50a..e2ef0eff 100644
--- a/examples/llava/README.md
+++ b/examples/llava/README.md
@@ -19,9 +19,9 @@ After building, run: `./llava-cli` to see the usage. For example:
**note**: A lower temperature like 0.1 is recommended for better quality. add `--temp 0.1` to the command to do so.
-## Model conversion
+## LLaVA 1.5
-- Clone `llava-v15-7b` and `clip-vit-large-patch14-336` locally:
+- Clone a LLaVA and a CLIP model ([available options](https://github.com/haotian-liu/LLaVA/blob/main/docs/MODEL_ZOO.md)). For example:
```sh
git clone https://huggingface.co/liuhaotian/llava-v1.5-7b
@@ -55,8 +55,14 @@ python ./convert.py ../llava-v1.5-7b
Now both the LLaMA part and the image encoder is in the `llava-v1.5-7b` directory.
+## LLaVA 1.6
+
+- Use `llava-surgery-v2.py`
+
+- TODO: add detailed instructions
+
## TODO
-- [ ] Support non-CPU backend for the image encoding part.
+- [x] Support non-CPU backend for the image encoding part.
- [ ] Support different sampling methods.
- [ ] Support more model variants.