Translation
Transformers
Safetensors
qwen3
text-generation
text-generation-inference
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Update README.md

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@@ -1,4 +1,8 @@
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  ---
 
 
 
 
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  language:
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  - en
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  - zh
@@ -24,7 +28,7 @@ language:
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  - hu
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  - id
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  - ko
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- - 'no'
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  - ro
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  - sk
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  - sv
@@ -60,15 +64,12 @@ language:
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  - ur
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  - uz
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  - yue
 
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  metrics:
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  - bleu
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  - comet
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- datasets:
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- - NiuTrans/LMT-60-sft-data
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- base_model:
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- - NiuTrans/LMT-60-4B-Base
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- license: apache-2.0
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  pipeline_tag: translation
 
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  ---
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  ## LMT
@@ -100,7 +101,9 @@ model_name = "NiuTrans/LMT-60-8B"
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  tokenizer = AutoTokenizer.from_pretrained(model_name, padding_side='left')
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  model = AutoModelForCausalLM.from_pretrained(model_name)
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- prompt = "Translate the following text from English into Chinese.\nEnglish: The concept came from China where plum blossoms were the flower of choice.\nChinese: "
 
 
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  messages = [{"role": "user", "content": prompt}]
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  text = tokenizer.apply_chat_template(
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  messages,
@@ -122,7 +125,7 @@ print("response:", outputs)
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  | Resource Tier | Languages |
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  | :---- | :---- |
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  | High-resource Languages (13) | Arabic(ar), English(en), Spanish(es), German(de), French(fr), Italian(it), Japanese(ja), Dutch(nl), Polish(pl), Portuguese(pt), Russian(ru), Turkish(tr), Chinese(zh) |
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- | Medium-resource Languages (18) | Bulgarian(bg), Bengali(bn), Czech(cs), Danish(da), Modern Greek(el), Persian(fa), Finnish(fi), Hindi(hi), Hungarian(hu), Indonesian(id), Korean(ko), Norwegian(no), Romanian(ro), Slovak(sk), Swedish(sv), Thai(th), Ukrainian(uk), Vietnamese(vi) |
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  | Low-resouce Languages (29) | Amharic(am), Azerbaijani(az), Tibetan(bo), Modern Hebrew(he), Croatian(hr), Armenian(hy), Icelandic(is), Javanese(jv), Georgian(ka), Kazakh(kk), Central Khmer(km), Kirghiz(ky), Lao(lo), Chinese Mongolian(mn_cn), Marathi(mr), Malay(ms), Burmese(my), Nepali(ne), Pashto(ps), Sinhala(si), Swahili(sw), Tamil(ta), Telugu(te), Tajik(tg), Tagalog(tl), Uighur(ug), Urdu(ur), Uzbek(uz), Yue Chinese(yue) |
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  ## Citation
 
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  ---
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+ base_model:
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+ - NiuTrans/LMT-60-8B-Base
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+ datasets:
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+ - NiuTrans/LMT-60-sft-data
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  language:
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  - en
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  - zh
 
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  - hu
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  - id
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  - ko
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+ - nb
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  - ro
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  - sk
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  - sv
 
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  - ur
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  - uz
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  - yue
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+ license: apache-2.0
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  metrics:
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  - bleu
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  - comet
 
 
 
 
 
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  pipeline_tag: translation
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+ library_name: transformers
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  ---
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  ## LMT
 
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  tokenizer = AutoTokenizer.from_pretrained(model_name, padding_side='left')
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  model = AutoModelForCausalLM.from_pretrained(model_name)
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+ prompt = "Translate the following text from English into Chinese.
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+ English: The concept came from China where plum blossoms were the flower of choice.
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+ Chinese: "
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  messages = [{"role": "user", "content": prompt}]
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  text = tokenizer.apply_chat_template(
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  messages,
 
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  | Resource Tier | Languages |
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  | :---- | :---- |
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  | High-resource Languages (13) | Arabic(ar), English(en), Spanish(es), German(de), French(fr), Italian(it), Japanese(ja), Dutch(nl), Polish(pl), Portuguese(pt), Russian(ru), Turkish(tr), Chinese(zh) |
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+ | Medium-resource Languages (18) | Bulgarian(bg), Bengali(bn), Czech(cs), Danish(da), Modern Greek(el), Persian(fa), Finnish(fi), Hindi(hi), Hungarian(hu), Indonesian(id), Korean(ko), Norwegian(nb), Romanian(ro), Slovak(sk), Swedish(sv), Thai(th), Ukrainian(uk), Vietnamese(vi) |
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  | Low-resouce Languages (29) | Amharic(am), Azerbaijani(az), Tibetan(bo), Modern Hebrew(he), Croatian(hr), Armenian(hy), Icelandic(is), Javanese(jv), Georgian(ka), Kazakh(kk), Central Khmer(km), Kirghiz(ky), Lao(lo), Chinese Mongolian(mn_cn), Marathi(mr), Malay(ms), Burmese(my), Nepali(ne), Pashto(ps), Sinhala(si), Swahili(sw), Tamil(ta), Telugu(te), Tajik(tg), Tagalog(tl), Uighur(ug), Urdu(ur), Uzbek(uz), Yue Chinese(yue) |
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  ## Citation