🚀 Project Introduction
This project is a text - generation model with a wide range of supported languages and programming languages. It has been tested on multiple datasets and shows performance in various NLP tasks.
📚 Documentation
Datasets
The model uses the following dataset:
Supported Languages
The model supports the following languages:
- ak, ar, as, bm, bn, ca, code, en, es, eu, fon, fr, gu, hi, id, ig, ki, kn, lg, ln, ml, mr, ne, nso, ny, or, pa, pt, rn, rw, sn, st, sw, ta, te, tn, ts, tum, tw, ur, vi, wo, xh, yo, zh, zu
Supported Programming Languages
The model supports the following programming languages:
- C, C++, C#, Go, Java, JavaScript, Lua, PHP, Python, Ruby, Rust, Scala, TypeScript
Pipeline Tag
Inference
Widget Examples
| Example Title |
Text |
| zh - en sentiment |
"A legendary beginning, an immortal myth. This is not just a movie, but a label for entering a new era, always inscribed in the annals of history. Would you rate the previous review as positive, neutral or negative?" |
| zh - zh sentiment |
"一个传奇的开端，一个不灭的神话，这不仅仅是一部电影，而是作为一个走进新时代的标签，永远彪炳史册。你认为这句话的立场是赞扬、中立还是批评？" |
| vi - en query |
"Suggest at least five related search terms to "Mạng neural nhân tạo"." |
| fr - fr query |
"Proposez au moins cinq mots clés concernant «Réseau de neurones artificiels»." |
| te - en qa |
"Explain in a sentence in Telugu what is backpropagation in neural networks." |
| en - en qa |
"Why is the sky blue?" |
| zh - en qa |
"Explain to me in Traditional Chinese what is the difference between Bitcoin and Ethereum." |
| code - en |
"Write a code snippet with O(log(n)) computational complexity." |
| es - en fable |
"Write a fairy tale about a troll saving a princess from a dangerous dragon. The fairy tale is a masterpiece that has achieved praise worldwide and its moral is "Heroes Come in All Shapes and Sizes". Story (in Spanish):" |
| hi - en fable |
"Write a fable about wood elves living in a forest that is suddenly invaded by ogres. The fable is a masterpiece that has achieved praise worldwide and its moral is "Violence is the last refuge of the incompetent". Fable (in Hindi):" |
| en - de - ar - fr - zh math |
"How many sides does a rectangle and heptagon have, when combined? Answer this question with some math. Ein Rechteck hat 4 Seiten. Ein Siebeneck hat 7 Seiten. In Kombination haben sie 4 + 7 = 11 Seiten. كم عدد الأضلاع التي يجمعها المربع والمثلث؟ Répondez à cette question en chinois." |
Model Index
The model named "bloomz" has the following performance results on different tasks and datasets:
Coreference Resolution
| Dataset |
Name |
Config |
Split |
Revision |
Accuracy |
| winogrande |
Winogrande XL (xl) |
xl |
validation |
a80f460359d1e9a67c006011c94de42a8759430c |
59.27 |
| Muennighoff/xwinograd |
XWinograd (en) |
en |
test |
9dd5ea5505fad86b7bedad667955577815300cee |
69.08 |
| Muennighoff/xwinograd |
XWinograd (fr) |
fr |
test |
9dd5ea5505fad86b7bedad667955577815300cee |
68.67 |
| Muennighoff/xwinograd |
XWinograd (jp) |
jp |
test |
9dd5ea5505fad86b7bedad667955577815300cee |
59.65 |
| Muennighoff/xwinograd |
XWinograd (pt) |
pt |
test |
9dd5ea5505fad86b7bedad667955577815300cee |
64.26 |
| Muennighoff/xwinograd |
XWinograd (ru) |
ru |
test |
9dd5ea5505fad86b7bedad667955577815300cee |
60.95 |
| Muennighoff/xwinograd |
XWinograd (zh) |
zh |
test |
9dd5ea5505fad86b7bedad667955577815300cee |
70.24 |
Natural Language Inference
| Dataset |
Name |
Config |
Split |
Revision |
Accuracy |
| anli |
ANLI (r1) |
r1 |
validation |
9dbd830a06fea8b1c49d6e5ef2004a08d9f45094 |
48.6 |
| anli |
ANLI (r2) |
r2 |
validation |
9dbd830a06fea8b1c49d6e5ef2004a08d9f45094 |
44.1 |
| anli |
ANLI (r3) |
r3 |
validation |
9dbd830a06fea8b1c49d6e5ef2004a08d9f45094 |
45.5 |
| super_glue |
SuperGLUE (cb) |
cb |
validation |
9e12063561e7e6c79099feb6d5a493142584e9e2 |
82.14 |
| super_glue |
SuperGLUE (rte) |
rte |
validation |
9e12063561e7e6c79099feb6d5a493142584e9e2 |
85.56 |
| xnli |
XNLI (ar) |
ar |
validation |
a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16 |
60.68 |
| xnli |
XNLI (bg) |
bg |
validation |
a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16 |
48.43 |
| xnli |
XNLI (de) |
de |
validation |
a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16 |
54.38 |
| xnli |
XNLI (el) |
el |
validation |
a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16 |
47.43 |
| xnli |
XNLI (en) |
en |
validation |
a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16 |
67.47 |
| xnli |
XNLI (es) |
es |
validation |
a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16 |
61.24 |
| xnli |
XNLI (fr) |
fr |
validation |
a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16 |
61.37 |
| xnli |
XNLI (hi) |
hi |
validation |
a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16 |
60.2 |
| xnli |
XNLI (ru) |
ru |
validation |
a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16 |
54.02 |
| xnli |
XNLI (sw) |
sw |
validation |
a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16 |
52.09 |
| xnli |
XNLI (th) |
th |
validation |
a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16 |
43.78 |
| xnli |
XNLI (tr) |
tr |
validation |
a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16 |
45.7 |
| xnli |
XNLI (ur) |
ur |
validation |
a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16 |
50.8 |
| xnli |
XNLI (vi) |
vi |
validation |
a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16 |
61.0 |
| xnli |
XNLI (zh) |
zh |
validation |
a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16 |
56.91 |
Program Synthesis
| Dataset |
Name |
Config |
Split |
Revision |
Pass@1 |
Pass@10 |
Pass@100 |
| openai_humaneval |
HumanEval |
None |
test |
e8dc562f5de170c54b5481011dd9f4fa04845771 |
12.06 |
26.53 |
48.44 |
Sentence Completion
| Dataset |
Name |
Config |
Split |
Revision |
Accuracy |
| story_cloze |
StoryCloze (2016) |
"2016" |
validation |
e724c6f8cdf7c7a2fb229d862226e15b023ee4db |
96.26 |
| super_glue |
SuperGLUE (copa) |
copa |
validation |
9e12063561e7e6c79099feb6d5a493142584e9e2 |
91.0 |
| xcopa |
XCOPA (et) |
et |
validation |
37f73c60fb123111fa5af5f9b705d0b3747fd187 |
51.0 |
| xcopa |
XCOPA (ht) |
ht |
validation |
37f73c60fb123111fa5af5f9b705d0b3747fd187 |
58.0 |
| xcopa |
XCOPA (id) |
id |
validation |
37f73c60fb123111fa5af5f9b705d0b3747fd187 |
86.0 |
| xcopa |
XCOPA (it) |
it |
validation |
37f73c60fb123111fa5af5f9b705d0b3747fd187 |
74.0 |
| xcopa |
XCOPA (qu) |
qu |
validation |
37f73c60fb123111fa5af5f9b705d0b3747fd187 |
56.0 |
| xcopa |
XCOPA (sw) |
sw |
validation |
37f73c60fb123111fa5af5f9b705d0b3747fd187 |
64.0 |
| xcopa |
XCOPA (ta) |
ta |
validation |
37f73c60fb123111fa5af5f9b705d0b3747fd187 |
69.0 |
| xcopa |
XCOPA (th) |
th |
validation |
37f73c60fb123111fa5af5f9b705d0b3747fd187 |
58.0 |
| xcopa |
XCOPA (tr) |
tr |
validation |
37f73c60fb123111fa5af5f9b705d0b3747fd187 |
57.0 |
| xcopa |
XCOPA (vi) |
vi |
validation |
37f73c60fb123111fa5af5f9b705d0b3747fd187 |
87.0 |
| xcopa |
XCOPA (zh) |
zh |
validation |
37f73c60fb123111fa5af5f9b705d0b3747fd187 |
90.0 |
| Muennighoff/xstory_cloze |
XStoryCloze (ar) |
ar |
validation |
8bb76e594b68147f1a430e86829d07189622b90d |
... |
License
- bigscience - bloom - rail - 1.0
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