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Model: maum-ai/Llama-3-MAAL-8B-Instruct-v0.1 Source: Original Platform
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README.md
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README.md
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---
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license: llama3
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base_model:
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- meta-llama/Meta-Llama-3-8B-Instruct
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language:
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- en
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- ko
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tags:
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- facebook
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- meta
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- llama
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- llama-3
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- llama-3-ko
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---
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<p align="left">
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<img src="https://cdn-uploads.huggingface.co/production/uploads/646484cfb90150b2706df03b/BEOyMpnnY9VY2KXlc3V2F.png" width="20%"/>
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<p>
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# Llama-3-MAAL-8B-Instruct-v0.1
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we release MAAL, Multilingual Adaptive Augmentation Language-model which comprises a groundbreaking fusion of multilingual capabilities and adaptive augmentation techniques.
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- **Developed by:** [maum.ai Brain NLP](https://maum-ai.github.io). Jaeyoon Jung, Jinjoo Lee, Yongjae Lee, Dongjun Lee, Woosung Joo
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- **Language(s) (NLP):** Korean, English (currently, bilingual)
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## Model Description
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Version 0.1 uses cross-lingual training to transfer instruction-following capabilities from English to Korean.
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- We Trained this model on an 8 H100-80G for 1 day with cross-lingual training dataset
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- we recommend using the fixed system prompt for the model unless you fine-tune it
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```
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너는 마음에이아이의 챗봇 MAAL이다. 고객의 질문에 친절하게 답하여라.
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```
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## sample inference code (GPU)
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```
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import transformers
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import torch
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model_id = "maum-ai/Llama-3-MAAL-8B-Instruct-v0.1"
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model = transformers.AutoModelForCausalLM.from_pretrained(model_id).to("cuda")
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tokenizer = transformers.AutoTokenizer.from_pretrained(model_id)
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streamer = transformers.TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
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# we recommend using the fixed prompt for the model unless you fine-tune it
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prompt = "너는 마음에이아이의 챗봇 MAAL이다. 고객의 질문에 친절하게 답하여라."
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instruction = "사과 한 박스에는 사과가 30개 들어있는데, 처음에는 사과 3박스가 있었고, 내가 사과 5개를 먹었어. 남은 사과는 총 몇개야?"
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messages = [
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{"role": "system", "content": f"{prompt}"},
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{"role": "user", "content": f"{instruction}"}
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]
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inputs = tokenizer.apply_chat_template(
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messages,
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tokenize=True,
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return_tensors='pt').to("cuda")
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outputs = model.generate(inputs, streamer=streamer, max_new_tokens=1024, pad_token_id=tokenizer.eos_token_id)
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```
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## Evaluation Results
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As the main goal of version 0.1 is to **transfer instruction-following capabilities from English to Korean** without utilizing continuous pre-training, etc., we select [**LogicKor**](https://github.com/StableFluffy/LogicKor) as our evaluation method to assess the Korean instruction skills.
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We compare our model with a similar parameter model (less than 13B) that has been fine-tuned on the Korean dataset. \* denotes our self-report result.
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|Model|single-turn(↑)|multi-turn(↑)|average(↑)|
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|-|-|-|-|
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|maum-ai/Llama-3-MAAL-8B-Instruct-v0.1*|**5.80**|4.66|**5.23**|
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|maywell/Synatra-kiqu-10.7B|5.71|4.73|5.22|
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|yanolja/EEVE-Korean-Instruct-10.8B-v1.0|5.78|3.92|4.85|
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|nlpai-lab/KULLM3|4.61|**4.83**|4.72|
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|MLP-KTLim/llama3-Bllossom*|2.11|1.57|1.84|
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## Limitations
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Due to this model being trained on a small dataset, it has several limitations.
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- Hard to generate diverse Korean texts
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- lack of Korean knowledge & Culture (localization)
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- Not work with Image inputs and video inputs
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## Todo
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we will solve these limitations one by one by upgrading this model like as...
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- Enhance the Korean generation through Vocabulary Expansion & Continuous pre-training. (more Korean corpus!)
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- Localize with cultural adaptation method and additional Korean knowledge data. [*similar idea*](https://aclanthology.org/2023.emnlp-main.18/)
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- Develop a Vision Language Model that can handle both video and image inputs. [*similar idea*](https://github.com/PKU-YuanGroup/Video-LLaVA)
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config.json
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{
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"_name_or_path": "/NAS_BRAIN/nlp/DEPLOY/Meta-Llama-3-8B-Instruct-CoITV2-3-ds1-finetune-v5",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 128000,
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"eos_token_id": 128001,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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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_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 500000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.37.2",
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"use_cache": false,
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"vocab_size": 128257
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}
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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
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"transformers_version": "4.37.2"
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}
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|
||||
"model.layers.8.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.9.input_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.norm.weight": "model-00004-of-00004.safetensors"
|
||||
}
|
||||
}
|
||||
23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<|begin_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "<|end_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<<|PAD|>>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
410571
tokenizer.json
Normal file
410571
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
2072
tokenizer_config.json
Normal file
2072
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user