Add LLaVA support (#2234)

* first commit

* llava

* clippy and fmt

* some fixes

* minor fixes

* remove useless file

* refactor: Remove llava/constants.rs and update llava/mod.rs

* modify variable name

* modify code after clippy

* Minor tweaks.

---------

Co-authored-by: laurent <laurent.mazare@gmail.com>

candle-examples/examples/llava/readme.md

@@ -0,0 +1,40 @@
+# candle-llava
+
+LLaVA (Large Language-and-Vision Assistant) is an end-to-end trained large
+multimodal model. This example is from [candle-llava](https://github.com/chenwanqq/candle-llava)
+
+The code is based on [https://github.com/haotian-liu/LLaVA](https://github.com/haotian-liu/LLaVA), Hence the llava-hf version of config may perform differently.
+
+## model zoo
+* [liuhaotian/LLaVA](https://huggingface.co/liuhaotian)
+* [llava-hf](https://huggingface.co/llava-hf)
+
+Right now this has been tested on `liuhaotian/llava-v1.6-vicuna-7b` and
+`llava-hf/llava-v1.6-vicuna-7b-hf`. Memory usage might have room for optimization.
+
+## Tokenizer Setup  
+The llava-hf models contain a `tokenizer.json` file so can be used directly with
+the `-hf` command line flag.
+
+For the original llava models, you can use the following code to generate the `tokenizer.json` file.
+
+```bash  
+conda create -n llava python=3.10  
+pip install transformers protobuf
+conda activate llava
+python -c "from transformers import AutoTokenizer;tokenizer=AutoTokenizer.from_pretrained('liuhaotian/llava-v1.6-vicuna-7b');tokenizer.save_pretrained('tokenizer')"
+```
+Then the `tokenizer.json` file should be in `tokenizer/tokenizer.json` (which is the default path).
+
+
+## eval
+
+```bash
+cargo run --example llava --features cuda -- --image-file "llava_logo.png" --prompt "is this a cat?" --hf # default args, use  llava-hf/llava-v1.6-vicuna-7b-hf. image-file is required^_^
+cargo run --example llava --features cuda -- --model-path liuhaotian/llava-v1.6-vicuna-7b  --image-file "llava_logo.png" --prompt "is this a cat?" # use liuhaotian/llava-v1.6-vicuna-7b, tokenizer setup should be done
+```
+
+## Major Limitations
+1. Currently only support llama-2/vicuna llm. Haven't supoort Mistral yet.
+2. There are some ops like split, nonzero and where are not supported by candle.
+3. Lack of quantization and LoRA support.