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Model: haoranxu/X-ALMA-13B-Group6 Source: Original Platform
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README.md
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---
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license: mit
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datasets:
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- oscar-corpus/OSCAR-2301
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- allenai/nllb
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- Helsinki-NLP/opus-100
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language:
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- en
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- ka
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- zh
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- ja
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- ko
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- fi
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- et
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base_model:
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- haoranxu/X-ALMA-13B-Pretrain
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---
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[X-ALMA](https://arxiv.org/pdf/2410.03115) builds upon [ALMA-R](https://arxiv.org/pdf/2401.08417) by expanding support from 6 to 50 languages. It utilizes a plug-and-play architecture with language-specific modules, complemented by a carefully designed training recipe. This release includes the **language-specific X-ALMA LoRA module and a merged model that supports the languages in Group 6: English (en), Georgian (ka), Chinese (zh), Japanese (ja), Korean (ko), Finnish (fi), and Estonian (et)**.
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```
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@misc{xu2024xalmaplugplay,
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title={X-ALMA: Plug & Play Modules and Adaptive Rejection for Quality Translation at Scale},
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author={Haoran Xu and Kenton Murray and Philipp Koehn and Hieu Hoang and Akiko Eriguchi and Huda Khayrallah},
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year={2024},
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eprint={2410.03115},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2410.03115},
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}
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```
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All X-ALMA checkpoints are released at huggingface:
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| Models | Model Link | Description |
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|:-------------:|:---------------:|:---------------:|
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| X-ALMA | [haoranxu/X-ALMA]([https://huggingface.co/haoranxu/ALMA-7B](https://huggingface.co/haoranxu/X-ALMA)) | X-ALMA model with all its modules |
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| X-ALMA-13B-Pretrain | [haoranxu/X-ALMA-13B-Pretrain](https://huggingface.co/haoranxu/X-ALMA-13B-Pretrain) | X-ALMA 13B multilingual pre-trained base model |
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| X-ALMA-Group1 | [haoranxu/X-ALMA-13B-Group1](https://huggingface.co/haoranxu/X-ALMA-13B-Group1) | X-ALMA group1 specific module and the merged model |
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| X-ALMA-Group2 | [haoranxu/X-ALMA-13B-Group2](https://huggingface.co/haoranxu/X-ALMA-13B-Group2) | X-ALMA group2 specific module and the merged model |
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| X-ALMA-Group3 | [haoranxu/X-ALMA-13B-Group3](https://huggingface.co/haoranxu/X-ALMA-13B-Group3) | X-ALMA group3 specific module and the merged model |
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| X-ALMA-Group4 | [haoranxu/X-ALMA-13B-Group4](https://huggingface.co/haoranxu/X-ALMA-13B-Group4) | X-ALMA group4 specific module and the merged model |
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| X-ALMA-Group5 | [haoranxu/X-ALMA-13B-Group5](https://huggingface.co/haoranxu/X-ALMA-13B-Group5) | X-ALMA group5 specific module and the merged model |
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| X-ALMA-Group6 | [haoranxu/X-ALMA-13B-Group6](https://huggingface.co/haoranxu/X-ALMA-13B-Group6) | X-ALMA group6 specific module and the merged model |
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| X-ALMA-Group7 | [haoranxu/X-ALMA-13B-Group7](https://huggingface.co/haoranxu/X-ALMA-13B-Group7) | X-ALMA group7 specific module and the merged model |
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| X-ALMA-Group8 | [haoranxu/X-ALMA-13B-Group8](https://huggingface.co/haoranxu/X-ALMA-13B-Group8) | X-ALMA group8 specific module and the merged model |
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## A quick start:
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There are three ways to load X-ALMA for translation. An example of translating "我爱机器翻译。" into English (X-ALMA should also able to do multilingual open-ended QA).
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**The first way**: loading the merged model where the language-specific module has been merged into the base model **(Recommended)**:
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```
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import torch
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from transformers import AutoModelForCausalLM
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from transformers import AutoTokenizer
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from peft import PeftModel
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GROUP2LANG = {
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1: ["da", "nl", "de", "is", "no", "sv", "af"],
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2: ["ca", "ro", "gl", "it", "pt", "es"],
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3: ["bg", "mk", "sr", "uk", "ru"],
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4: ["id", "ms", "th", "vi", "mg", "fr"],
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5: ["hu", "el", "cs", "pl", "lt", "lv"],
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6: ["ka", "zh", "ja", "ko", "fi", "et"],
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7: ["gu", "hi", "mr", "ne", "ur"],
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8: ["az", "kk", "ky", "tr", "uz", "ar", "he", "fa"],
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}
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LANG2GROUP = {lang: str(group) for group, langs in GROUP2LANG.items() for lang in langs}
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group_id = LANG2GROUP["zh"]
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model = AutoModelForCausalLM.from_pretrained(f"haoranxu/X-ALMA-13B-Group{group_id}", torch_dtype=torch.float16, device_map="auto")
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tokenizer = AutoTokenizer.from_pretrained(f"haoranxu/X-ALMA-13B-Group{group_id}", padding_side='left')
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# Add the source sentence into the prompt template
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prompt="Translate this from Chinese to English:\nChinese: 我爱机器翻译。\nEnglish:"
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# X-ALMA needs chat template but ALMA and ALMA-R don't need it.
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chat_style_prompt = [{"role": "user", "content": prompt}]
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prompt = tokenizer.apply_chat_template(chat_style_prompt, tokenize=False, add_generation_prompt=True)
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input_ids = tokenizer(prompt, return_tensors="pt", padding=True, max_length=40, truncation=True).input_ids.cuda()
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# Translation
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with torch.no_grad():
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generated_ids = model.generate(input_ids=input_ids, num_beams=5, max_new_tokens=20, do_sample=True, temperature=0.6, top_p=0.9)
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outputs = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
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print(outputs)
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```
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**The second way**: loading the base model and language-specific module **(Recommended)**:
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```
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model = AutoModelForCausalLM.from_pretrained("haoranxu/X-ALMA-13B-Pretrain", torch_dtype=torch.float16, device_map="auto")
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model = PeftModel.from_pretrained(model, f"haoranxu/X-ALMA-13B-Group{group_id}")
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tokenizer = AutoTokenizer.from_pretrained(f"haoranxu/X-ALMA-13B-Group{group_id}", padding_side='left')
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```
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**The third way**: loading the base model with all language-specific modules like MoE: (Require large GPU memory)
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```
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from modeling_xalma import XALMAForCausalLM
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model = XALMAForCausalLM.from_pretrained("haoranxu/X-ALMA", torch_dtype=torch.float16, device_map="auto")
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tokenizer = AutoTokenizer.from_pretrained("haoranxu/X-ALMA", padding_side='left')
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# Add `lang="zh"`: specify the language to instruct the model on which group to use for the third loading method during generation.
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generated_ids = model.generate(input_ids=input_ids, num_beams=5, max_new_tokens=20, do_sample=True, temperature=0.6, top_p=0.9, lang="zh")
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```
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||||
}
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||||
}
|
||||
30
special_tokens_map.json
Normal file
30
special_tokens_map.json
Normal file
@@ -0,0 +1,30 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
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|
||||
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|
||||
"single_word": false
|
||||
},
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<unk>",
|
||||
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|
||||
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|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
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|
||||
"content": "<unk>",
|
||||
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|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
93404
tokenizer.json
Normal file
93404
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
3
tokenizer.model
Normal file
3
tokenizer.model
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:7aedb3582ecda9fa99ee9242c17a9658f6744db083ee6ebdc8fb14857f84d220
|
||||
size 499723
|
||||
45
tokenizer_config.json
Normal file
45
tokenizer_config.json
Normal file
@@ -0,0 +1,45 @@
|
||||
{
|
||||
"add_bos_token": true,
|
||||
"add_eos_token": false,
|
||||
"add_prefix_space": true,
|
||||
"added_tokens_decoder": {
|
||||
"0": {
|
||||
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|
||||
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|
||||
"normalized": false,
|
||||
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|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"1": {
|
||||
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|
||||
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|
||||
"normalized": false,
|
||||
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|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"2": {
|
||||
"content": "</s>",
|
||||
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|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"bos_token": "<s>",
|
||||
"chat_template": "{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if loop.index0 == 0 and system_message != false %}{% set content = '<<SYS>>\\n' + system_message + '\\n<</SYS>>\\n\\n' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ bos_token + '[INST] ' + content.strip() + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{content.strip() + eos_token }}{% endif %}{% endfor %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "</s>",
|
||||
"legacy": false,
|
||||
"model_max_length": 1000000000000000019884624838656,
|
||||
"pad_token": "<unk>",
|
||||
"padding_side": "left",
|
||||
"sp_model_kwargs": {},
|
||||
"spaces_between_special_tokens": false,
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"unk_token": "<unk>",
|
||||
"use_default_system_prompt": false,
|
||||
"use_fast": true
|
||||
}
|
||||
Reference in New Issue
Block a user