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Ct2fast M2m100 12B Last Ckpt by michaelfeil

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Model Card on HF 🤗: https://huggingface.co/michaelfeil/ct2fast-m2m100-12B-last-ckpt 

Ct2fast M2m100 12B Last Ckpt Benchmarks

LLME Score: 0.10403
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Ct2fast M2m100 12B Last Ckpt (michaelfeil/ct2fast-m2m100-12B-last-ckpt)

Ct2fast M2m100 12B Last Ckpt Parameters and Internals

Model Type 
multilingual translation, encoder-decoder, seq-to-seq
Use Cases 
Areas:
multilingual translation
Applications:
chatbots, content localization, cross-language information retrieval
Primary Use Cases:
Translating text from one language to another among the 100 supported languages, Generating translations in multiple directions, covering 9,900 possible language pairs
Limitations:
Dependent on the quality and diversity of training data, May not accurately translate idiomatic expressions or dialect-specific content
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 
Data Volume:
Unknown
Methodology:
Seq-to-seq training
Model Architecture:
Multilingual encoder-decoder
Input Output 
Input Format:
Text input as source language
Accepted Modalities:
text
Output Format:
Text output in target language
Performance Tips:
Int8 quantization for faster inference on CPUs, float16 on GPUs.
Release Notes 
Version:
12B
Date:
unknown
Notes:
Introduction of the M2M100 model with 12B parameters for many-to-many multilingual translation capabilities.
LLM NameCt2fast M2m100 12B Last Ckpt
Repository 🤗https://huggingface.co/michaelfeil/ct2fast-m2m100-12B-last-ckpt 
Model Size12b
Required VRAM23.6 GB
Updated2025-01-24
Maintainermichaelfeil
Model Files  23.6 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
Language Codesm2m100
Licensemit
Model Max Length1024
Tokenizer ClassM2M100Tokenizer
Padding Token<pad>

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Note: green Score (e.g. "73.2") means that the model is better than michaelfeil/ct2fast-m2m100-12B-last-ckpt.

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