732 lines
22 KiB
Markdown
732 lines
22 KiB
Markdown
---
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base_model: bigscience/bloomz-3b
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datasets:
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- bigscience/xP3
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language:
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- ak
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- ar
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- as
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- bm
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- bn
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- ca
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- code
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- en
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- es
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- eu
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- fon
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- fr
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- gu
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- hi
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- id
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- ig
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- ki
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- kn
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- lg
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- ln
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- ml
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- mr
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- ne
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- nso
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- ny
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- or
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- pa
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- pt
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- rn
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- rw
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- sn
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- st
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- sw
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- ta
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- te
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- tn
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- ts
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- tum
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- tw
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- ur
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- vi
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- wo
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- xh
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- yo
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- zh
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- zu
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license: bigscience-bloom-rail-1.0
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pipeline_tag: text-generation
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tags:
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- llama-cpp
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- matrixportal
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programming_language:
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- C
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- C++
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- C#
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- Go
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- Java
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- JavaScript
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- Lua
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- PHP
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- Python
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- Ruby
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- Rust
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- Scala
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- TypeScript
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widget:
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- 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
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review as positive, neutral or negative?
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example_title: zh-en sentiment
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- 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？
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example_title: zh-zh sentiment
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- text: Suggest at least five related search terms to "Mạng neural nhân tạo".
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example_title: vi-en query
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- text: Proposez au moins cinq mots clés concernant «Réseau de neurones artificiels».
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example_title: fr-fr query
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- text: Explain in a sentence in Telugu what is backpropagation in neural networks.
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example_title: te-en qa
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- text: Why is the sky blue?
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example_title: en-en qa
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- text: 'Write a fairy tale about a troll saving a princess from a dangerous dragon.
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The fairy tale is a masterpiece that has achieved praise worldwide and its moral
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is "Heroes Come in All Shapes and Sizes". Story (in Spanish):'
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example_title: es-en fable
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- text: 'Write a fable about wood elves living in a forest that is suddenly invaded
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by ogres. The fable is a masterpiece that has achieved praise worldwide and its
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moral is "Violence is the last refuge of the incompetent". Fable (in Hindi):'
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example_title: hi-en fable
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model-index:
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- name: bloomz-3b1
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results:
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- task:
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type: Coreference resolution
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dataset:
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name: Winogrande XL (xl)
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type: winogrande
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config: xl
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split: validation
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revision: a80f460359d1e9a67c006011c94de42a8759430c
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metrics:
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- type: Accuracy
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value: 53.67
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- task:
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type: Coreference resolution
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dataset:
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name: XWinograd (en)
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type: Muennighoff/xwinograd
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config: en
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split: test
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revision: 9dd5ea5505fad86b7bedad667955577815300cee
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metrics:
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- type: Accuracy
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value: 59.23
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- task:
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type: Coreference resolution
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dataset:
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name: XWinograd (fr)
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type: Muennighoff/xwinograd
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config: fr
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split: test
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revision: 9dd5ea5505fad86b7bedad667955577815300cee
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metrics:
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- type: Accuracy
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value: 53.01
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- task:
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type: Coreference resolution
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dataset:
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name: XWinograd (jp)
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type: Muennighoff/xwinograd
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config: jp
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split: test
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revision: 9dd5ea5505fad86b7bedad667955577815300cee
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metrics:
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- type: Accuracy
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value: 52.45
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- task:
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type: Coreference resolution
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dataset:
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name: XWinograd (pt)
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type: Muennighoff/xwinograd
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config: pt
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split: test
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revision: 9dd5ea5505fad86b7bedad667955577815300cee
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metrics:
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- type: Accuracy
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value: 53.61
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- task:
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type: Coreference resolution
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dataset:
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name: XWinograd (ru)
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type: Muennighoff/xwinograd
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config: ru
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split: test
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revision: 9dd5ea5505fad86b7bedad667955577815300cee
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metrics:
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- type: Accuracy
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value: 53.97
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- task:
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type: Coreference resolution
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dataset:
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name: XWinograd (zh)
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type: Muennighoff/xwinograd
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config: zh
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split: test
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revision: 9dd5ea5505fad86b7bedad667955577815300cee
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metrics:
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- type: Accuracy
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value: 60.91
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- task:
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type: Natural language inference
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dataset:
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name: ANLI (r1)
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type: anli
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config: r1
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split: validation
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revision: 9dbd830a06fea8b1c49d6e5ef2004a08d9f45094
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metrics:
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- type: Accuracy
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value: 40.1
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- task:
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type: Natural language inference
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dataset:
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name: ANLI (r2)
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type: anli
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config: r2
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split: validation
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revision: 9dbd830a06fea8b1c49d6e5ef2004a08d9f45094
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metrics:
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- type: Accuracy
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value: 36.8
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- task:
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type: Natural language inference
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dataset:
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name: ANLI (r3)
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type: anli
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config: r3
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split: validation
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revision: 9dbd830a06fea8b1c49d6e5ef2004a08d9f45094
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metrics:
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- type: Accuracy
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value: 40.0
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- task:
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type: Natural language inference
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dataset:
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name: SuperGLUE (cb)
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type: super_glue
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config: cb
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split: validation
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revision: 9e12063561e7e6c79099feb6d5a493142584e9e2
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metrics:
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- type: Accuracy
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value: 75.0
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- task:
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type: Natural language inference
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dataset:
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name: SuperGLUE (rte)
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type: super_glue
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config: rte
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split: validation
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revision: 9e12063561e7e6c79099feb6d5a493142584e9e2
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metrics:
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- type: Accuracy
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value: 76.17
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- task:
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type: Natural language inference
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dataset:
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name: XNLI (ar)
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type: xnli
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config: ar
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split: validation
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revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
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metrics:
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- type: Accuracy
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value: 53.29
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- task:
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type: Natural language inference
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dataset:
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name: XNLI (bg)
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type: xnli
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config: bg
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split: validation
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revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
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metrics:
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- type: Accuracy
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value: 43.82
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- task:
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type: Natural language inference
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dataset:
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name: XNLI (de)
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type: xnli
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config: de
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split: validation
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revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
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metrics:
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- type: Accuracy
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value: 45.26
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- task:
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type: Natural language inference
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dataset:
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name: XNLI (el)
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type: xnli
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config: el
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split: validation
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revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
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metrics:
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- type: Accuracy
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value: 42.61
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- task:
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type: Natural language inference
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dataset:
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name: XNLI (en)
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type: xnli
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config: en
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split: validation
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revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
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metrics:
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- type: Accuracy
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value: 57.31
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- task:
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type: Natural language inference
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dataset:
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name: XNLI (es)
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type: xnli
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config: es
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split: validation
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revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
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metrics:
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- type: Accuracy
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value: 56.14
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- task:
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type: Natural language inference
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dataset:
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name: XNLI (fr)
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type: xnli
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config: fr
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split: validation
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revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
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metrics:
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- type: Accuracy
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value: 55.78
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- task:
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type: Natural language inference
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dataset:
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name: XNLI (hi)
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type: xnli
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config: hi
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split: validation
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revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
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metrics:
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- type: Accuracy
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value: 51.49
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- task:
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type: Natural language inference
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dataset:
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name: XNLI (ru)
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type: xnli
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config: ru
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split: validation
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revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
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metrics:
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- type: Accuracy
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value: 47.11
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- task:
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type: Natural language inference
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dataset:
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name: XNLI (sw)
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type: xnli
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config: sw
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split: validation
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revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
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metrics:
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- type: Accuracy
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value: 47.83
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- task:
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type: Natural language inference
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dataset:
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name: XNLI (th)
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type: xnli
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config: th
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split: validation
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revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
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metrics:
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- type: Accuracy
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value: 42.93
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- task:
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type: Natural language inference
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dataset:
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name: XNLI (tr)
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type: xnli
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config: tr
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split: validation
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revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
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metrics:
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- type: Accuracy
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value: 37.23
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- task:
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type: Natural language inference
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dataset:
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name: XNLI (ur)
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type: xnli
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config: ur
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split: validation
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revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
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metrics:
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- type: Accuracy
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value: 49.04
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- task:
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type: Natural language inference
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dataset:
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name: XNLI (vi)
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type: xnli
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config: vi
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split: validation
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revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
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metrics:
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- type: Accuracy
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value: 53.98
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- task:
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type: Natural language inference
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dataset:
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name: XNLI (zh)
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type: xnli
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config: zh
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split: validation
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revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
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metrics:
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- type: Accuracy
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value: 54.18
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- task:
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type: Program synthesis
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dataset:
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name: HumanEval
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type: openai_humaneval
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config: None
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split: test
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revision: e8dc562f5de170c54b5481011dd9f4fa04845771
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metrics:
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- type: Pass@1
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value: 6.29
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- type: Pass@10
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value: 11.94
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- type: Pass@100
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value: 19.06
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- task:
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type: Sentence completion
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dataset:
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name: StoryCloze (2016)
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type: story_cloze
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config: '2016'
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split: validation
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revision: e724c6f8cdf7c7a2fb229d862226e15b023ee4db
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metrics:
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- type: Accuracy
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value: 87.33
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- task:
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type: Sentence completion
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dataset:
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name: SuperGLUE (copa)
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type: super_glue
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config: copa
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split: validation
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revision: 9e12063561e7e6c79099feb6d5a493142584e9e2
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metrics:
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- type: Accuracy
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value: 76.0
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- task:
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type: Sentence completion
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dataset:
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name: XCOPA (et)
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type: xcopa
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config: et
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split: validation
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revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
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metrics:
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- type: Accuracy
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value: 53.0
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- task:
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type: Sentence completion
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dataset:
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name: XCOPA (ht)
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type: xcopa
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config: ht
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split: validation
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revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
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metrics:
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- type: Accuracy
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value: 64.0
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- task:
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type: Sentence completion
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dataset:
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name: XCOPA (id)
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type: xcopa
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config: id
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split: validation
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revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
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metrics:
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- type: Accuracy
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value: 70.0
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- task:
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type: Sentence completion
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dataset:
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name: XCOPA (it)
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type: xcopa
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config: it
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split: validation
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revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
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metrics:
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- type: Accuracy
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value: 53.0
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- task:
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type: Sentence completion
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dataset:
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name: XCOPA (qu)
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type: xcopa
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config: qu
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split: validation
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revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
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metrics:
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- type: Accuracy
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value: 56.0
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- task:
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type: Sentence completion
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dataset:
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name: XCOPA (sw)
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type: xcopa
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config: sw
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split: validation
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revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
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metrics:
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- type: Accuracy
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value: 66.0
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- task:
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type: Sentence completion
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dataset:
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name: XCOPA (ta)
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type: xcopa
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config: ta
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split: validation
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revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
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metrics:
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- type: Accuracy
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value: 59.0
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- task:
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type: Sentence completion
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dataset:
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name: XCOPA (th)
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type: xcopa
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config: th
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split: validation
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revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
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metrics:
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- type: Accuracy
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value: 63.0
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- task:
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type: Sentence completion
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dataset:
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name: XCOPA (tr)
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type: xcopa
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config: tr
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split: validation
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revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
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metrics:
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- type: Accuracy
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value: 61.0
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- task:
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type: Sentence completion
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dataset:
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name: XCOPA (vi)
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type: xcopa
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config: vi
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split: validation
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revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
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metrics:
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- type: Accuracy
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value: 77.0
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- task:
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type: Sentence completion
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dataset:
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name: XCOPA (zh)
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type: xcopa
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config: zh
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split: validation
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revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
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metrics:
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- type: Accuracy
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value: 73.0
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- task:
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type: Sentence completion
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dataset:
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name: XStoryCloze (ar)
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type: Muennighoff/xstory_cloze
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config: ar
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split: validation
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||
revision: 8bb76e594b68147f1a430e86829d07189622b90d
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||
metrics:
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||
- type: Accuracy
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||
value: 80.61
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- task:
|
||
type: Sentence completion
|
||
dataset:
|
||
name: XStoryCloze (es)
|
||
type: Muennighoff/xstory_cloze
|
||
config: es
|
||
split: validation
|
||
revision: 8bb76e594b68147f1a430e86829d07189622b90d
|
||
metrics:
|
||
- type: Accuracy
|
||
value: 85.9
|
||
- task:
|
||
type: Sentence completion
|
||
dataset:
|
||
name: XStoryCloze (eu)
|
||
type: Muennighoff/xstory_cloze
|
||
config: eu
|
||
split: validation
|
||
revision: 8bb76e594b68147f1a430e86829d07189622b90d
|
||
metrics:
|
||
- type: Accuracy
|
||
value: 70.95
|
||
- task:
|
||
type: Sentence completion
|
||
dataset:
|
||
name: XStoryCloze (hi)
|
||
type: Muennighoff/xstory_cloze
|
||
config: hi
|
||
split: validation
|
||
revision: 8bb76e594b68147f1a430e86829d07189622b90d
|
||
metrics:
|
||
- type: Accuracy
|
||
value: 78.89
|
||
- task:
|
||
type: Sentence completion
|
||
dataset:
|
||
name: XStoryCloze (id)
|
||
type: Muennighoff/xstory_cloze
|
||
config: id
|
||
split: validation
|
||
revision: 8bb76e594b68147f1a430e86829d07189622b90d
|
||
metrics:
|
||
- type: Accuracy
|
||
value: 82.99
|
||
- task:
|
||
type: Sentence completion
|
||
dataset:
|
||
name: XStoryCloze (my)
|
||
type: Muennighoff/xstory_cloze
|
||
config: my
|
||
split: validation
|
||
revision: 8bb76e594b68147f1a430e86829d07189622b90d
|
||
metrics:
|
||
- type: Accuracy
|
||
value: 49.9
|
||
- task:
|
||
type: Sentence completion
|
||
dataset:
|
||
name: XStoryCloze (ru)
|
||
type: Muennighoff/xstory_cloze
|
||
config: ru
|
||
split: validation
|
||
revision: 8bb76e594b68147f1a430e86829d07189622b90d
|
||
metrics:
|
||
- type: Accuracy
|
||
value: 61.42
|
||
- task:
|
||
type: Sentence completion
|
||
dataset:
|
||
name: XStoryCloze (sw)
|
||
type: Muennighoff/xstory_cloze
|
||
config: sw
|
||
split: validation
|
||
revision: 8bb76e594b68147f1a430e86829d07189622b90d
|
||
metrics:
|
||
- type: Accuracy
|
||
value: 69.69
|
||
- task:
|
||
type: Sentence completion
|
||
dataset:
|
||
name: XStoryCloze (te)
|
||
type: Muennighoff/xstory_cloze
|
||
config: te
|
||
split: validation
|
||
revision: 8bb76e594b68147f1a430e86829d07189622b90d
|
||
metrics:
|
||
- type: Accuracy
|
||
value: 73.66
|
||
- task:
|
||
type: Sentence completion
|
||
dataset:
|
||
name: XStoryCloze (zh)
|
||
type: Muennighoff/xstory_cloze
|
||
config: zh
|
||
split: validation
|
||
revision: 8bb76e594b68147f1a430e86829d07189622b90d
|
||
metrics:
|
||
- type: Accuracy
|
||
value: 84.32
|
||
---
|
||
|
||
# ysn-rfd/bloomz-3b-GGUF
|
||
This model was converted to GGUF format from [`bigscience/bloomz-3b`](https://huggingface.co/bigscience/bloomz-3b) using llama.cpp via the ggml.ai's [all-gguf-same-where](https://huggingface.co/spaces/matrixportal/all-gguf-same-where) space.
|
||
Refer to the [original model card](https://huggingface.co/bigscience/bloomz-3b) for more details on the model.
|
||
|
||
## ✅ Quantized Models Download List
|
||
|
||
### 🔍 Recommended Quantizations
|
||
- **✨ General CPU Use:** [`Q4_K_M`](https://huggingface.co/ysn-rfd/bloomz-3b-GGUF/resolve/main/bloomz-3b-q4_k_m.gguf) (Best balance of speed/quality)
|
||
- **📱 ARM Devices:** [`Q4_0`](https://huggingface.co/ysn-rfd/bloomz-3b-GGUF/resolve/main/bloomz-3b-q4_0.gguf) (Optimized for ARM CPUs)
|
||
- **🏆 Maximum Quality:** [`Q8_0`](https://huggingface.co/ysn-rfd/bloomz-3b-GGUF/resolve/main/bloomz-3b-q8_0.gguf) (Near-original quality)
|
||
|
||
### 📦 Full Quantization Options
|
||
| 🚀 Download | 🔢 Type | 📝 Notes |
|
||
|:---------|:-----|:------|
|
||
| [Download](https://huggingface.co/ysn-rfd/bloomz-3b-GGUF/resolve/main/bloomz-3b-q2_k.gguf) |  | Basic quantization |
|
||
| [Download](https://huggingface.co/ysn-rfd/bloomz-3b-GGUF/resolve/main/bloomz-3b-q3_k_s.gguf) |  | Small size |
|
||
| [Download](https://huggingface.co/ysn-rfd/bloomz-3b-GGUF/resolve/main/bloomz-3b-q3_k_m.gguf) |  | Balanced quality |
|
||
| [Download](https://huggingface.co/ysn-rfd/bloomz-3b-GGUF/resolve/main/bloomz-3b-q3_k_l.gguf) |  | Better quality |
|
||
| [Download](https://huggingface.co/ysn-rfd/bloomz-3b-GGUF/resolve/main/bloomz-3b-q4_0.gguf) |  | Fast on ARM |
|
||
| [Download](https://huggingface.co/ysn-rfd/bloomz-3b-GGUF/resolve/main/bloomz-3b-q4_k_s.gguf) |  | Fast, recommended |
|
||
| [Download](https://huggingface.co/ysn-rfd/bloomz-3b-GGUF/resolve/main/bloomz-3b-q4_k_m.gguf) |  ⭐ | Best balance |
|
||
| [Download](https://huggingface.co/ysn-rfd/bloomz-3b-GGUF/resolve/main/bloomz-3b-q5_0.gguf) |  | Good quality |
|
||
| [Download](https://huggingface.co/ysn-rfd/bloomz-3b-GGUF/resolve/main/bloomz-3b-q5_k_s.gguf) |  | Balanced |
|
||
| [Download](https://huggingface.co/ysn-rfd/bloomz-3b-GGUF/resolve/main/bloomz-3b-q5_k_m.gguf) |  | High quality |
|
||
| [Download](https://huggingface.co/ysn-rfd/bloomz-3b-GGUF/resolve/main/bloomz-3b-q6_k.gguf) |  🏆 | Very good quality |
|
||
| [Download](https://huggingface.co/ysn-rfd/bloomz-3b-GGUF/resolve/main/bloomz-3b-q8_0.gguf) |  ⚡ | Fast, best quality |
|
||
| [Download](https://huggingface.co/ysn-rfd/bloomz-3b-GGUF/resolve/main/bloomz-3b-f16.gguf) |  | Maximum accuracy |
|
||
|
||
💡 **Tip:** Use `F16` for maximum precision when quality is critical
|
||
|
||
|
||
---
|
||
# 🚀 Applications and Tools for Locally Quantized LLMs
|
||
## 🖥️ Desktop Applications
|
||
|
||
| Application | Description | Download Link |
|
||
|-----------------|----------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------|
|
||
| **Llama.cpp** | A fast and efficient inference engine for GGUF models. | [GitHub Repository](https://github.com/ggml-org/llama.cpp) |
|
||
| **Ollama** | A streamlined solution for running LLMs locally. | [Website](https://ollama.com/) |
|
||
| **AnythingLLM** | An AI-powered knowledge management tool. | [GitHub Repository](https://github.com/Mintplex-Labs/anything-llm) |
|
||
| **Open WebUI** | A user-friendly web interface for running local LLMs. | [GitHub Repository](https://github.com/open-webui/open-webui) |
|
||
| **GPT4All** | A user-friendly desktop application supporting various LLMs, compatible with GGUF models. | [GitHub Repository](https://github.com/nomic-ai/gpt4all) |
|
||
| **LM Studio** | A desktop application designed to run and manage local LLMs, supporting GGUF format. | [Website](https://lmstudio.ai/) |
|
||
| **GPT4All Chat**| A chat application compatible with GGUF models for local, offline interactions. | [GitHub Repository](https://github.com/nomic-ai/gpt4all) |
|
||
|
||
---
|
||
|
||
## 📱 Mobile Applications
|
||
|
||
| Application | Description | Download Link |
|
||
|-------------------|----------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------|
|
||
| **ChatterUI** | A simple and lightweight LLM app for mobile devices. | [GitHub Repository](https://github.com/Vali-98/ChatterUI) |
|
||
| **Maid** | Mobile Artificial Intelligence Distribution for running AI models on mobile devices. | [GitHub Repository](https://github.com/Mobile-Artificial-Intelligence/maid) |
|
||
| **PocketPal AI** | A mobile AI assistant powered by local models. | [GitHub Repository](https://github.com/a-ghorbani/pocketpal-ai) |
|
||
| **Layla** | A flexible platform for running various AI models on mobile devices. | [Website](https://www.layla-network.ai/) |
|
||
|
||
---
|
||
|
||
## 🎨 Image Generation Applications
|
||
|
||
| Application | Description | Download Link |
|
||
|-------------------------------------|----------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------|
|
||
| **Stable Diffusion** | An open-source AI model for generating images from text. | [GitHub Repository](https://github.com/CompVis/stable-diffusion) |
|
||
| **Stable Diffusion WebUI** | A web application providing access to Stable Diffusion models via a browser interface. | [GitHub Repository](https://github.com/AUTOMATIC1111/stable-diffusion-webui) |
|
||
| **Local Dream** | Android Stable Diffusion with Snapdragon NPU acceleration. Also supports CPU inference. | [GitHub Repository](https://github.com/xororz/local-dream) |
|
||
| **Stable-Diffusion-Android (SDAI)** | An open-source AI art application for Android devices, enabling digital art creation. | [GitHub Repository](https://github.com/ShiftHackZ/Stable-Diffusion-Android) |
|
||
|
||
---
|
||
|