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Model: deepvk/llava-saiga-8b Source: Original Platform
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README.md
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---
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library_name: transformers
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license: apache-2.0
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datasets:
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- deepvk/LLaVA-Instruct-ru
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- Lin-Chen/ShareGPT4V
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- deepvk/GQA-ru
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language:
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- ru
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- en
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base_model: IlyaGusev/saiga_llama3_8b
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pipeline_tag: image-text-to-text
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---
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# LLaVA-Saiga-8b
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LLaVA-Saiga-8b is a Vision-Language Model (VLM) based on [`IlyaGusev/saiga_llama3_8b`](https://huggingface.co/IlyaGusev/saiga_llama3_8b) model
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and trained in original LLaVA setup. This model is primarily adapted to work with Russian, but still capable to work with English.
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## Usage
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Model usage is simple via `transformers` API
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```python
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import requests
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from PIL import Image
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from transformers import AutoProcessor, AutoTokenizer, LlavaForConditionalGeneration
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model_name = "deepvk/llava-saiga-8b"
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model = LlavaForConditionalGeneration.from_pretrained(model_name)
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processor = AutoProcessor.from_pretrained(model_name)
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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url = "https://www.ilankelman.org/stopsigns/australia.jpg"
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img = Image.open(requests.get(url, stream=True).raw)
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messages = [
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{"role": "user", "content": "<image>\nОпиши картинку несколькими словами."}
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]
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text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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inputs = processor(images=[img], text=text, return_tensors="pt")
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generate_ids = model.generate(**inputs, max_new_tokens=30)
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answer = tokenizer.decode(generate_ids[0, inputs.input_ids.shape[1]:], skip_special_tokens=True)
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print(answer)
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```
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Use the `<image>` tag to point to an image in the text and follow the chat template for a multi-turn conversation.
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The model is capable of chatting without any images or working with multiple images in a conversation, but this behavior has not been tested.
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The model format allows it to be directly used in popular frameworks,
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e.g. you can test the model using [lmms-eval](https://github.com/EvolvingLMMs-Lab/lmms-eval), see Results section for details.
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## Train
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To train this model, we follow the original LLaVA pipeline and reuse [`haotian-liu/LLaVA`](https://github.com/haotian-liu/LLaVA) framework.
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The model was trained in two stages:
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1. The adapter was trained using pre-training data from [`ShareGPT4V`](https://github.com/InternLM/InternLM-XComposer/tree/main/projects/ShareGPT4V).
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2. Instruction tuning included training the LLM and the adapter, for this we use:
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* [`deepvk/LLaVA-Instruct-ru`](https://huggingface.co/datasets/deepvk/LLaVA-Instruct-ru) - our new dataset of VLM instructions in Russian
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* [`deepvk/GQA-ru`](https://huggingface.co/datasets/deepvk/GQA-ru) - the training part of the popular GQA test, translated into Russian, we used the post-prompt "Ответь одним словом. ".
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* We also used instruction data from ShareGPT4V.
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The entire training process took 3-4 days on 8 x A100 80GB.
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## Results
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The model's performance was evaluated using [`lmms-eval`](https://github.com/EvolvingLMMs-Lab/lmms-eval/tree/main) framework
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```bash
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accelerate launch -m lmms_eval --model llava_hf --model_args pretrained="deepvk/llava-saiga-8b" \
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--tasks gqa-ru,mmbench_ru_dev,gqa,mmbench_en_dev --batch_size 1 \
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--log_samples --log_samples_suffix llava-saiga-8b --output_path ./logs/
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```
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| Model | GQA | GQA-ru | MMBench | MMBench-ru |
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| ----------------------------------------------------------------------------------------------- |:---------:|:---------:|:---------:|:----------:|
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| [`deepvk/llava-gemma-2b-lora`](https://huggingface.co/deepvk/llava-gemma-2b-lora) | 56.39 | 46.37 | 51.72 | 40.19 |
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| [`Intel/llava-gemma-2b`](https://huggingface.co/Intel/llava-gemma-2b) | 59.80 | 0.20 | 39.40 | 28.30 |
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| `deepvk/llava-saiga-8b` [this model] | 62.00 | **51.44** | 64.26 | **56.65** |
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| [`llava-hf/llava-1.5-7b-hf`](https://huggingface.co/llava-hf/llava-1.5-7b-hf) | 61.31 | 28.39 | 62.97 | 52.25 |
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| [`llava-hf/llava-v1.6-mistral-7b-hf`](https://huggingface.co/llava-hf/llava-v1.6-mistral-7b-hf) | **64.65** | 6.65 | **67.70** | 48.80 |
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*Note*: for MMBench we didn't use OpenAI API for finding quantifier in generated string. Therefore, the score is similar to Exact Match as in GQA benchmark.
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## Citation
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```
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@misc{liu2023llava,
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title={Visual Instruction Tuning},
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author={Liu, Haotian and Li, Chunyuan and Wu, Qingyang and Lee, Yong Jae},
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publisher={NeurIPS},
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year={2023},
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}
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```
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```
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@misc{deepvk2024llava-saiga-8b,
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title={LLaVA-Saiga-8b},
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author={Belopolskih, Daniil and Spirin, Egor},
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url={https://huggingface.co/deepvk/llava-saiga-8b},
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publisher={Hugging Face}
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year={2024},
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}
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```
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config.json
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{
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"_name_or_path": "llavahf_saiga",
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"architectures": [
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"LlavaForConditionalGeneration"
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],
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"ignore_index": -100,
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"image_token_index": 128256,
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"model_type": "llava",
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"pad_token_id": 128257,
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"projector_hidden_act": "gelu",
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"text_config": {
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"_name_or_path": "IlyaGusev/saiga_llama3_8b",
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"architectures": [
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"LlamaForCausalLM"
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],
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"eos_token_id": 128001,
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"intermediate_size": 14336,
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"max_position_embeddings": 8192,
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"model_type": "llama",
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"rope_theta": 500000.0,
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"torch_dtype": "bfloat16",
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"vocab_size": 128320
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},
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"torch_dtype": "float16",
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"transformers_version": "4.42.4",
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"vision_config": {
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"hidden_size": 1024,
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"image_size": 336,
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"intermediate_size": 4096,
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"model_type": "clip_vision_model",
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"num_attention_heads": 16,
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"num_hidden_layers": 24,
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"patch_size": 14,
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"projection_dim": 768,
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"vocab_size": 32000
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},
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"vision_feature_layer": -2,
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"vision_feature_select_strategy": "default"
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}
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||||
28
preprocessor_config.json
Normal file
28
preprocessor_config.json
Normal file
@@ -0,0 +1,28 @@
|
||||
{
|
||||
"crop_size": {
|
||||
"height": 336,
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}
|
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4
processor_config.json
Normal file
4
processor_config.json
Normal file
@@ -0,0 +1,4 @@
|
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{
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|
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"processor_class": "LlavaProcessor"
|
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}
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23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
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{
|
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|
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|
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|
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}
|
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3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:64e61f13441f4693892f4c085860f5f75f144ea58df50c5a33de7c79c07cce4c
|
||||
size 9086064
|
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2081
tokenizer_config.json
Normal file
2081
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user