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Ct2fast M2m100 1.2B by michaelfeil

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Model Card on HF 🤗: https://huggingface.co/michaelfeil/ct2fast-m2m100_1.2B 

Ct2fast M2m100 1.2B Benchmarks

LLME Score: 0.09216
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Ct2fast M2m100 1.2B (michaelfeil/ct2fast-m2m100_1.2B)
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Ct2fast M2m100 1.2B Parameters and Internals

Model Type 
multilingual, machine translation
Additional Notes 
M2M100 can translate directly between 9,900 direction pairs of 100 languages. Requires `sentencepiece` for tokenization.
Supported Languages 
af (Afrikaans), am (Amharic), ar (Arabic), ast (Asturian), az (Azerbaijani), ba (Bashkir), be (Belarusian), bg (Bulgarian), bn (Bengali), br (Breton), bs (Bosnian), ca (Catalan; Valencian), ceb (Cebuano), cs (Czech), cy (Welsh), da (Danish), de (German), el (Greeek), en (English), es (Spanish), et (Estonian), fa (Persian), ff (Fulah), fi (Finnish), fr (French), fy (Western Frisian), ga (Irish), gd (Gaelic; Scottish Gaelic), gl (Galician), gu (Gujarati), ha (Hausa), he (Hebrew), hi (Hindi), hr (Croatian), ht (Haitian; Haitian Creole), hu (Hungarian), hy (Armenian), id (Indonesian), ig (Igbo), ilo (Iloko), is (Icelandic), it (Italian), ja (Japanese), jv (Javanese), ka (Georgian), kk (Kazakh), km (Central Khmer), kn (Kannada), ko (Korean), lb (Luxembourgish; Letzeburgesch), lg (Ganda), ln (Lingala), lo (Lao), lt (Lithuanian), lv (Latvian), mg (Malagasy), mk (Macedonian), ml (Malayalam), mn (Mongolian), mr (Marathi), ms (Malay), my (Burmese), ne (Nepali), nl (Dutch; Flemish), no (Norwegian), ns (Northern Sotho), oc (Occitan (post 1500)), or (Oriya), pa (Panjabi; Punjabi), pl (Polish), ps (Pushto; Pashto), pt (Portuguese), ro (Romanian; Moldavian; Moldovan), ru (Russian), sd (Sindhi), si (Sinhala; Sinhalese), sk (Slovak), sl (Slovenian), so (Somali), sq (Albanian), sr (Serbian), ss (Swati), su (Sundanese), sv (Swedish), sw (Swahili), ta (Tamil), th (Thai), tl (Tagalog), tn (Tswana), tr (Turkish), uk (Ukrainian), ur (Urdu), uz (Uzbek), vi (Vietnamese), wo (Wolof), xh (Xhosa), yi (Yiddish), yo (Yoruba), zh (Chinese), zu (Zulu)
Training Details 
Model Architecture:
M2M100 is a multilingual encoder-decoder (seq-to-seq) model trained for Many-to-Many multilingual translation.
Input Output 
Input Format:
Tokens
Accepted Modalities:
text
Output Format:
Tokens/Translated Text
Performance Tips:
Use int8 inference for speedup on supported devices.
LLM NameCt2fast M2m100 1.2B
Repository 🤗https://huggingface.co/michaelfeil/ct2fast-m2m100_1.2B 
Model Size1.2b
Required VRAM2.5 GB
Updated2025-08-17
Maintainermichaelfeil
Model Files  2.5 GB
Supported Languagesaf am ar az ba be bg bn br bs ca cs cy da de el en es et fa ff fi fr fy ga gd gl gu ha he hi hr ht hu hy id ig is it ja jv ka kk km kn ko lb lg ln lo lt lv mg mk ml mn mr ms my ne nl ns oc or pa pl ps pt ro ru sd si sk sl so sq sr ss su sv sw ta th tl tn tr uk ur uz vi wo xh yi yo zh zu
Model ArchitectureAutoModel
Licensemit
Padding Token<pad>

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