Text Generation
Transformers
llm-rs
ggml
Inference Endpoints
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+ ---
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+ datasets:
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+ - bigscience/xP3
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+ license: bigscience-bloom-rail-1.0
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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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+ 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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+ tags:
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+ - llm-rs
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+ - ggml
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+ pipeline_tag: text-generation
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+ ---
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+
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+ # GGML covnerted Models of [BigScience](https://huggingface.co/bigscience)'s Bloom models
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+
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+ ## Description
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+
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+ > We present BLOOMZ & mT0, a family of models capable of following human instructions in dozens of languages zero-shot. We finetune BLOOM & mT5 pretrained multilingual language models on our crosslingual task mixture (xP3) and find the resulting models capable of crosslingual generalization to unseen tasks & languages.
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+
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+ - **Repository:** [bigscience-workshop/xmtf](https://github.com/bigscience-workshop/xmtf)
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+ - **Paper:** [Crosslingual Generalization through Multitask Finetuning](https://arxiv.org/abs/2211.01786)
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+ - **Point of Contact:** [Niklas Muennighoff](mailto:niklas@hf.co)
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+ - **Languages:** Refer to [bloom](https://huggingface.co/bigscience/bloom) for pretraining & [xP3](https://huggingface.co/datasets/bigscience/xP3) for finetuning language proportions. It understands both pretraining & finetuning languages.
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+
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+ ### Intended use
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+
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+ We recommend using the model to perform tasks expressed in natural language. For example, given the prompt "*Translate to English: Je t’aime.*", the model will most likely answer "*I love you.*". Some prompt ideas from our paper:
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+ - 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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+ - Suggest at least five related search terms to "Mạng neural nhân tạo".
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+ - 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):
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+ - Explain in a sentence in Telugu what is backpropagation in neural networks.
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+
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+ ## Converted Models
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+ | Name | Based on | Type | Container | GGML Version |
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+ |:----------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------|:-------|:------------|:---------------|
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+ | [bloomz-1b1-f16.bin](https://huggingface.co/rustformers/bloomz-ggml/blob/main/bloomz-1b1-f16.bin) | [bigscience/bloomz-1b1](https://huggingface.co/bigscience/bloomz-1b1) | F16 | GGML | V3 |
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+ | [bloomz-1b1-q4_0.bin](https://huggingface.co/rustformers/bloomz-ggml/blob/main/bloomz-1b1-q4_0.bin) | [bigscience/bloomz-1b1](https://huggingface.co/bigscience/bloomz-1b1) | Q4_0 | GGML | V3 |
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+ | [bloomz-1b1-q4_0-ggjt.bin](https://huggingface.co/rustformers/bloomz-ggml/blob/main/bloomz-1b1-q4_0-ggjt.bin) | [bigscience/bloomz-1b1](https://huggingface.co/bigscience/bloomz-1b1) | Q4_0 | GGJT | V3 |
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+ | [bloomz-1b1-q5_1-ggjt.bin](https://huggingface.co/rustformers/bloomz-ggml/blob/main/bloomz-1b1-q5_1-ggjt.bin) | [bigscience/bloomz-1b1](https://huggingface.co/bigscience/bloomz-1b1) | Q5_1 | GGJT | V3 |
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+ | [bloomz-1b7-f16.bin](https://huggingface.co/rustformers/bloomz-ggml/blob/main/bloomz-1b7-f16.bin) | [bigscience/bloomz-1b7](https://huggingface.co/bigscience/bloomz-1b7) | F16 | GGML | V3 |
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+ | [bloomz-1b7-q4_0.bin](https://huggingface.co/rustformers/bloomz-ggml/blob/main/bloomz-1b7-q4_0.bin) | [bigscience/bloomz-1b7](https://huggingface.co/bigscience/bloomz-1b7) | Q4_0 | GGML | V3 |
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+ | [bloomz-1b7-q4_0-ggjt.bin](https://huggingface.co/rustformers/bloomz-ggml/blob/main/bloomz-1b7-q4_0-ggjt.bin) | [bigscience/bloomz-1b7](https://huggingface.co/bigscience/bloomz-1b7) | Q4_0 | GGJT | V3 |
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+ | [bloomz-1b7-q5_1-ggjt.bin](https://huggingface.co/rustformers/bloomz-ggml/blob/main/bloomz-1b7-q5_1-ggjt.bin) | [bigscience/bloomz-1b7](https://huggingface.co/bigscience/bloomz-1b7) | Q5_1 | GGJT | V3 |
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+ | [bloomz-3b-f16.bin](https://huggingface.co/rustformers/bloomz-ggml/blob/main/bloomz-3b-f16.bin) | [bigscience/bloomz-3b](https://huggingface.co/bigscience/bloomz-3b) | F16 | GGML | V3 |
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+ | [bloomz-3b-q4_0.bin](https://huggingface.co/rustformers/bloomz-ggml/blob/main/bloomz-3b-q4_0.bin) | [bigscience/bloomz-3b](https://huggingface.co/bigscience/bloomz-3b) | Q4_0 | GGML | V3 |
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+ | [bloomz-3b-q4_0-ggjt.bin](https://huggingface.co/rustformers/bloomz-ggml/blob/main/bloomz-3b-q4_0-ggjt.bin) | [bigscience/bloomz-3b](https://huggingface.co/bigscience/bloomz-3b) | Q4_0 | GGJT | V3 |
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+ | [bloomz-3b-q5_1-ggjt.bin](https://huggingface.co/rustformers/bloomz-ggml/blob/main/bloomz-3b-q5_1-ggjt.bin) | [bigscience/bloomz-3b](https://huggingface.co/bigscience/bloomz-3b) | Q5_1 | GGJT | V3 |
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+ | [bloomz-560m-f16.bin](https://huggingface.co/rustformers/bloomz-ggml/blob/main/bloomz-560m-f16.bin) | [bigscience/bloomz-560m](https://huggingface.co/bigscience/bloomz-560m) | F16 | GGML | V3 |
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+ | [bloomz-560m-q4_0.bin](https://huggingface.co/rustformers/bloomz-ggml/blob/main/bloomz-560m-q4_0.bin) | [bigscience/bloomz-560m](https://huggingface.co/bigscience/bloomz-560m) | Q4_0 | GGML | V3 |
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+ | [bloomz-560m-q4_0-ggjt.bin](https://huggingface.co/rustformers/bloomz-ggml/blob/main/bloomz-560m-q4_0-ggjt.bin) | [bigscience/bloomz-560m](https://huggingface.co/bigscience/bloomz-560m) | Q4_0 | GGJT | V3 |
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+ | [bloomz-560m-q5_1-ggjt.bin](https://huggingface.co/rustformers/bloomz-ggml/blob/main/bloomz-560m-q5_1-ggjt.bin) | [bigscience/bloomz-560m](https://huggingface.co/bigscience/bloomz-560m) | Q5_1 | GGJT | V3 |
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+
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+ ## Usage
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+
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+ ### Python via [llm-rs](https://github.com/LLukas22/llm-rs-python):
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+
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+ #### Installation
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+ Via pip: `pip install llm-rs`
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+
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+ #### Run inference
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+ ```python
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+ from llm_rs import AutoModel
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+
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+ #Load the model, define any model you like from the list above as the `model_file`
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+ model = AutoModel.from_pretrained("rustformers/bloomz-ggml",model_file="bloomz-3b-q4_0-ggjt.bin")
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+
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+ #Generate
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+ print(model.generate("The meaning of life is"))
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+ ```
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+
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+ ### Rust via [Rustformers/llm](https://github.com/rustformers/llm):
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+
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+ #### Installation
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+ ```
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+ git clone --recurse-submodules https://github.com/rustformers/llm.git
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+ cd llm
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+ cargo build --release
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+ ```
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+
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+ #### Run inference
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+ ```
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+ cargo run --release -- bloom infer -m path/to/model.bin -p "Tell me how cool the Rust programming language is:"
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+ ```