Model: tensorblock/bloomz-560m-GGUF
Author: tensorblock
Pipeline: text-generation
Tags: gguf, TensorBlock, GGUF, text-generation, 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, dataset:bigscience/xP3, base_model:bigscience/bloomz-560m, base_model:quantized:bigscience/bloomz-560m, license:bigscience-bloom-rail-1.0, model-index, endpoints_compatible, region:us
Base models (quantized): id: bigscience/bloomz-560m
Card metadata: datasets: bigscience/xP3
license: bigscience-bloom-rail-1.0
language: 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
programming_language: C, C++, C#, Go, Java, JavaScript, Lua, PHP, Python, Ruby, Rust, Scala, TypeScript
pipeline_tag: text-generation
widget: text: 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。Would you rate the previous review as positive, neutral or negative?
example_title: zh-en sentiment, text: 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？
example_title: zh-zh sentiment, text: Suggest at least five related search terms to "Mạng neural nhân tạo".
example_title: vi-en query, text: Proposez au moins cinq mots clés concernant «Réseau de neurones artificiels».
example_title: fr-fr query, text: Explain in a sentence in Telugu what is backpropagation in neural networks.
example_title: te-en qa, text: Why is the sky blue?
example_title: en-en qa, text: 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):
example_title: es-en fable, text: 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):
example_title: hi-en fable
base_model: bigscience/bloomz-560m
tags: TensorBlock, GGUF
model-index: name: bloomz-560m
results: task: type: Coreference resolution
dataset: name: Winogrande XL (xl)
type: winogrande
config: xl
split: validation
revision: a80f460359d1e9a67c006011c94de42a8759430c
metrics: type: Accuracy
value: 52.41
verified: no, task: type: Coreference resolution
dataset: name: XWinograd (en)
type: Muennighoff/xwinograd
config: en
split: test
revision: 9dd5ea5505fad86b7bedad667955577815300cee
metrics: type: Accuracy
value: 51.01
verified: no, task: type: Coreference resolution
dataset: name: XWinograd (fr)
type: Muennighoff/xwinograd
config: fr
split: test
revision: 9dd5ea5505fad86b7bedad667955577815300cee
metrics: type: Accuracy
value: 51.81
verified: no, task: type: Coreference resolution
dataset: name: XWinograd (jp)
type: Muennighoff/xwinograd
config: jp
split: test
revision: 9dd5ea5505fad86b7bedad667955577815300cee
metrics: type: Accuracy
value: 52.03
verified: no, task: type: Coreference resolution
dataset: name: XWinograd (pt)
type: Muennighoff/xwinograd
config: pt
split: test
revision: 9dd5ea5505fad86b7bedad667955577815300cee
metrics: type: Accuracy
value: 53.99
verified: no, task: type: Coreference resolution
dataset: name: XWinograd (ru)
type: Muennighoff/xwinograd
config: ru
split: test
revision: 9dd5ea5505fad86b7bedad667955577815300cee
metrics: type: Accuracy
value: 53.97
verified: no, task: type: Coreference resolution
dataset: name: XWinograd (zh)
type: Muennighoff/xwinograd
config: zh
split: test
revision: 9dd5ea5505fad86b7bedad667955577815300cee
metrics: type: Accuracy
value: 54.76
verified: no, task: type: Natural language inference
dataset: name: ANLI (r1)
type: anli
config: r1
split: validation
revision: 9dbd830a06fea8b1c49d6e5ef2004a08d9f45094
metrics: type: Accuracy
value: 33.4
verified: no, task: type: Natural language inference
dataset: name: ANLI (r2)
type: anli
config: r2
split: validation
revision: 9dbd830a06fea8b1c49d6e5ef2004a08d9f45094
metrics: type: Accuracy
value: 33.4
verified: no, task: type: Natural language inference
dataset: name: ANLI (r3)
type: anli
config: r3
split: validation
revision: 9dbd830a06fea8b1c49d6e5ef2004a08d9f45094
metrics: type: Accuracy
value: 33.5
verified: no, task: type: Natural language inference
dataset: name: SuperGLUE (cb)
type: super_glue
config: cb
split: validation
revision: 9e12063561e7e6c79099feb6d5a493142584e9e2
metrics: type: Accuracy
value: 53.57
verified: no, task: type: Natural language inference
dataset: name: SuperGLUE (rte)
type: super_glue
config: rte
split: validation
revision: 9e12063561e7e6c79099feb6d5a493142584e9e2
metrics: type: Accuracy
value: 67.15
verified: no, task: type: Natural language inference
dataset: name: XNLI (ar)
type: xnli
config: ar
split: validation
revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
metrics: type: Accuracy
value: 44.46
verified: no, task: type: Natural language inference
dataset: name: XNLI (bg)
type: xnli
config: bg
split: validation
revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
metrics: type: Accuracy
value: 39.76
verified: no, task: type: Natural language inference
dataset: name: XNLI (de)
type: xnli
config: de
split: validation
revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
metrics: type: Accuracy
value: 39.36
verified: no, task: type: Natural language inference
dataset: name: XNLI (el)
type: xnli
config: el
split: validation
revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
metrics: type: Accuracy
value: 40.96
verified: no, task: type: Natural language inference
dataset: name: XNLI (en)
type: xnli
config: en
split: validation
revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
metrics: type: Accuracy
value: 46.43
verified: no, task: type: Natural language inference
dataset: name: XNLI (es)
type: xnli
config: es
split: validation
revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
metrics: type: Accuracy
value: 44.98
verified: no, task: type: Natural language inference
dataset: name: XNLI (fr)
type: xnli
config: fr
split: validation
revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
metrics: type: Accuracy
value: 45.54
verified: no, task: type: Natural language inference
dataset: name: XNLI (hi)
type: xnli
config: hi
split: validation
revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
metrics: type: Accuracy
value: 41.81
verified: no, task: type: Natural language inference
dataset: name: XNLI (ru)
type: xnli
config: ru
split: validation
revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
metrics: type: Accuracy
value: 39.64
verified: no, task: type: Natural language inference
dataset: name: XNLI (sw)
type: xnli
config: sw
split: validation
revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
metrics: type: Accuracy
value: 38.35
verified: no, task: type: Natural language inference
dataset: name: XNLI (th)
type: xnli
config: th
split: validation
revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
metrics: type: Accuracy
value: 35.5
verified: no, task: type: Natural language inference
dataset: name: XNLI (tr)
type: xnli
config: tr
split: validation
revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
metrics: type: Accuracy
value: 37.31
verified: no, task: type: Natural language inference
dataset: name: XNLI (ur)
type: xnli
config: ur
split: validation
revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
metrics: type: Accuracy
value: 38.96
verified: no, task: type: Natural language inference
dataset: name: XNLI (vi)
type: xnli
config: vi
split: validation
revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
metrics: type: Accuracy
value: 44.74
verified: no, task: type: Natural language inference
dataset: name: XNLI (zh)
type: xnli
config: zh
split: validation
revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
metrics: type: Accuracy
value: 44.66
verified: no, task: type: Program synthesis
dataset: name: HumanEval
type: openai_humaneval
config: None
split: test
revision: e8dc562f5de170c54b5481011dd9f4fa04845771
metrics: type: Pass@1
value: 2.18
verified: no, type: Pass@10
value: 4.11
verified: no, type: Pass@100
value: 9
verified: no, task: type: Sentence completion
dataset: name: StoryCloze (2016)
type: story_cloze
config: 2016
split: validation
revision: e724c6f8cdf7c7a2fb229d862226e15b023ee4db
metrics: type: Accuracy
value: 60.29
verified: no, task: type: Sentence completion
dataset: name: SuperGLUE (copa)
type: super_glue
config: copa
split: validation
revision: 9e12063561e7e6c79099feb6d5a493142584e9e2
metrics: type: Accuracy
value: 52
verified: no, task: type: Sentence completion
dataset: name: XCOPA (et)
type: xcopa
config: et
split: validation
revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
metrics: type: Accuracy
value: 53
verified: no, task: type: Sentence completion
dataset: name: XCOPA (ht)
type: xcopa
config: ht
split: validation
revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
metrics: type: Accuracy
value: 49
verified: no, task: type: Sentence completion
dataset: name: XCOPA (id)
type: xcopa
config: id
split: validation
revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
metrics: type: Accuracy
value: 57
verified: no, task: type: Sentence completion
dataset: name: XCOPA (it)
type: xcopa
config: it
split: validation
revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
metrics: type: Accuracy
value: 52
verified: no, task: type: Sentence completion
dataset: name: XCOPA (qu)
type: xcopa
config: qu
split: validation
revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
metrics: type: Accuracy
value: 55
verified: no, task: type: Sentence completion
dataset: name: XCOPA (sw)
type: xcopa
config: sw
split: validation
revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
metrics: type: Accuracy
value: 56
verified: no, task: type: Sentence completion
dataset: name: XCOPA (ta)
type: xcopa
config: ta
split: validation
revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
metrics: type: Accuracy
value: 58
verified: no, task: type: Sentence completion
dataset: name: XCOPA (th)
type: xcopa
config: th
split: validation
revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
metrics: type: Accuracy
value: 58
verified: no, task: type: Sentence completion
dataset: name: XCOPA (tr)
type: xcopa
config: tr
split: validation
revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
metrics: type: Accuracy
value: 61
verified: no, task: type: Sentence completion
dataset: name: XCOPA (vi)
type: xcopa
config: vi
split: validation
revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
metrics: type: Accuracy
value: 61
verified: no, task: type: Sentence completion
dataset: name: XCOPA (zh)
type: xcopa
config: zh
split: validation
revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
metrics: type: Accuracy
value: 61
verified: no, task: type: Sentence completion
dataset: name: XStoryCloze (ar)
type: Muennighoff/xstory_cloze
config: ar
split: validation
revision: 8bb76e594b68147f1a430e86829d07189622b90d
metrics: type: Accuracy
value: 54.4
verified: no, task: type: Sentence completion
dataset: name: XStoryCloze (es)
type: Muennighoff/xstory_cloze
config: es
split: validation
revision: 8bb76e594b68147f1a430e86829d07189622b90d
metrics: type: Accuracy
value: 56.45
verified: no, task: type: Sentence completion
dataset: name: XStoryCloze (eu)
type: Muennighoff/xstory_cloze
config: eu
split: validation
revision: 8bb76e594b68147f1a430e86829d07189622b90d
metrics: type: Accuracy
value: 50.56
verified: no, task: type: Sentence completion
dataset: name: XStoryCloze (hi)
type: Muennighoff/xstory_cloze
config: hi
split: validation
revision: 8bb76e594b68147f1a430e86829d07189622b90d
metrics: type: Accuracy
value: 55.79
verified: no, task: type: Sentence completion
dataset: name: XStoryCloze (id)
type: Muennighoff/xstory_cloze
config: id
split: validation
revision: 8bb76e594b68147f1a430e86829d07189622b90d
metrics: type: Accuracy
value: 57.84
verified: no, task: type: Sentence completion
dataset: name: XStoryCloze (my)
type: Muennighoff/xstory_cloze
config: my
split: validation
revision: 8bb76e594b68147f1a430e86829d07189622b90d
metrics: type: Accuracy
value: 47.05
verified: no, task: type: Sentence completion
dataset: name: XStoryCloze (ru)
type: Muennighoff/xstory_cloze
config: ru
split: validation
revision: 8bb76e594b68147f1a430e86829d07189622b90d
metrics: type: Accuracy
value: 53.14
verified: no, task: type: Sentence completion
dataset: name: XStoryCloze (sw)
type: Muennighoff/xstory_cloze
config: sw
split: validation
revision: 8bb76e594b68147f1a430e86829d07189622b90d
metrics: type: Accuracy
value: 51.36
verified: no, task: type: Sentence completion
dataset: name: XStoryCloze (te)
type: Muennighoff/xstory_cloze
config: te
split: validation
revision: 8bb76e594b68147f1a430e86829d07189622b90d
metrics: type: Accuracy
value: 54.86
verified: no, task: type: Sentence completion
dataset: name: XStoryCloze (zh)
type: Muennighoff/xstory_cloze
config: zh
split: validation
revision: 8bb76e594b68147f1a430e86829d07189622b90d
metrics: type: Accuracy
value: 56.52
verified: no
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Created: 2024-11-11 15:15:06