madlad400-8b-lm / README.md
jbochi's picture
Update README.md
c6a3b5b
|
raw
history blame
3.94 kB
metadata
license: apache-2.0
language:
  - en
  - ru
  - es
  - fr
  - de
  - it
  - pt
  - pl
  - nl
  - vi
  - tr
  - sv
  - id
  - ro
  - cs
  - zh
  - hu
  - ja
  - th
  - fi
  - fa
  - uk
  - da
  - el
  - 'no'
  - bg
  - sk
  - ko
  - ar
  - lt
  - ca
  - sl
  - he
  - et
  - lv
  - hi
  - sq
  - ms
  - az
  - sr
  - ta
  - hr
  - kk
  - is
  - ml
  - mr
  - te
  - af
  - gl
  - fil
  - be
  - mk
  - eu
  - bn
  - ka
  - mn
  - bs
  - uz
  - ur
  - sw
  - yue
  - ne
  - kn
  - kaa
  - gu
  - si
  - cy
  - eo
  - la
  - hy
  - ky
  - tg
  - ga
  - mt
  - my
  - km
  - tt
  - so
  - ku
  - ps
  - pa
  - rw
  - lo
  - ha
  - dv
  - fy
  - lb
  - ckb
  - mg
  - gd
  - am
  - ug
  - ht
  - grc
  - hmn
  - sd
  - jv
  - mi
  - tk
  - ceb
  - yi
  - ba
  - fo
  - or
  - xh
  - su
  - kl
  - ny
  - sm
  - sn
  - co
  - zu
  - ig
  - yo
  - pap
  - st
  - haw
  - as
  - oc
  - cv
  - lus
  - tet
  - gsw
  - sah
  - br
  - rm
  - sa
  - bo
  - om
  - se
  - ce
  - cnh
  - ilo
  - hil
  - udm
  - os
  - lg
  - ti
  - vec
  - ts
  - tyv
  - kbd
  - ee
  - iba
  - av
  - kha
  - to
  - tn
  - nso
  - fj
  - zza
  - ak
  - ada
  - otq
  - dz
  - bua
  - cfm
  - ln
  - chm
  - gn
  - krc
  - wa
  - hif
  - yua
  - srn
  - war
  - rom
  - bik
  - pam
  - sg
  - lu
  - ady
  - kbp
  - syr
  - ltg
  - myv
  - iso
  - kac
  - bho
  - ay
  - kum
  - qu
  - za
  - pag
  - ngu
  - ve
  - pck
  - zap
  - tyz
  - hui
  - bbc
  - tzo
  - tiv
  - ksd
  - gom
  - min
  - ang
  - nhe
  - bgp
  - nzi
  - nnb
  - nv
  - zxx
  - bci
  - kv
  - new
  - mps
  - alt
  - meu
  - bew
  - fon
  - iu
  - abt
  - mgh
  - mnw
  - tvl
  - dov
  - tlh
  - ho
  - kw
  - mrj
  - meo
  - crh
  - mbt
  - emp
  - ace
  - ium
  - mam
  - gym
  - mai
  - crs
  - pon
  - ubu
  - fip
  - quc
  - gv
  - kj
  - btx
  - ape
  - chk
  - rcf
  - shn
  - tzh
  - mdf
  - ppk
  - ss
  - gag
  - cab
  - kri
  - seh
  - ibb
  - tbz
  - bru
  - enq
  - ach
  - cuk
  - kmb
  - wo
  - kek
  - qub
  - tab
  - bts
  - kos
  - rwo
  - cak
  - tuc
  - bum
  - cjk
  - gil
  - stq
  - tsg
  - quh
  - mak
  - arn
  - ban
  - jiv
  - sja
  - yap
  - tcy
  - toj
  - twu
  - xal
  - amu
  - rmc
  - hus
  - nia
  - kjh
  - bm
  - guh
  - mas
  - acf
  - dtp
  - ksw
  - bzj
  - din
  - zne
  - mad
  - msi
  - mag
  - mkn
  - kg
  - lhu
  - ch
  - qvi
  - mh
  - djk
  - sus
  - mfe
  - srm
  - dyu
  - ctu
  - gui
  - pau
  - inb
  - bi
  - mni
  - guc
  - jam
  - wal
  - jac
  - bas
  - gor
  - skr
  - nyu
  - noa
  - sda
  - gub
  - nog
  - cni
  - teo
  - tdx
  - sxn
  - rki
  - nr
  - frp
  - alz
  - taj
  - lrc
  - cce
  - rn
  - jvn
  - hvn
  - nij
  - dwr
  - izz
  - msm
  - bus
  - ktu
  - chr
  - maz
  - tzj
  - suz
  - knj
  - bim
  - gvl
  - bqc
  - tca
  - pis
  - prk
  - laj
  - mel
  - qxr
  - niq
  - ahk
  - shp
  - hne
  - spp
  - koi
  - krj
  - quf
  - luz
  - agr
  - tsc
  - mqy
  - gof
  - gbm
  - miq
  - dje
  - awa
  - bjj
  - qvz
  - sjp
  - tll
  - raj
  - kjg
  - bgz
  - quy
  - cbk
  - akb
  - oj
  - ify
  - mey
  - ks
  - cac
  - brx
  - qup
  - syl
  - jax
  - ff
  - ber
  - tks
  - trp
  - mrw
  - adh
  - smt
  - srr
  - ffm
  - qvc
  - mtr
  - ann
  - kaa
  - aa
  - noe
  - nut
  - gyn
  - kwi
  - xmm
  - msb
library_name: transformers
tags:
  - text-generation-inference
datasets:
  - allenai/MADLAD-400
pipeline_tag: translation

This model has the safetensors weights for Madlad-400 8B param language model.

There's currently no Python code to run inference. See details in this thread

Available language models models:

Article: MADLAD-400: A Multilingual And Document-Level Large Audited Dataset

Abstract:

We introduce MADLAD-400, a manually audited, general domain 3T token monolingual dataset based on CommonCrawl, spanning 419 languages. We discuss the limitations revealed by self-auditing MADLAD-400, and the role data auditing had in the dataset creation process. We then train and release a 10.7B-parameter multilingual machine translation model on 250 billion tokens covering over 450 languages using publicly available data, and find that it is competitive with models that are significantly larger, and report the results on different domains. In addition, we train a 8B-parameter language model, and assess the results on few-shot translation. We make the baseline models available to the research community.