--- license: apache-2.0 inference: false datasets: - CohereForAI/xP3x - CohereForAI/aya_dataset - CohereForAI/aya_collection - DataProvenanceInitiative/Commercially-Verified-Licenses - CohereForAI/aya_evaluation_suite language: - afr - amh - ara - aze - bel - ben - bul - cat - ceb - ces - cym - dan - deu - ell - eng - epo - est - eus - fin - fil - fra - fry - gla - gle - glg - guj - hat - hau - heb - hin - hun - hye - ibo - ind - isl - ita - jav - jpn - kan - kat - kaz - khm - kir - kor - kur - lao - lav - lat - lit - ltz - mal - mar - mkd - mlg - mlt - mon - mri - msa - mya - nep - nld - nor - nso - nya - ory - pan - pes - pol - por - pus - ron - rus - sin - slk - slv - smo - sna - snd - som - sot - spa - sqi - srp - sun - swa - swe - tam - tel - tgk - tha - tur - twi - ukr - urd - uzb - vie - xho - yid - yor - zho - zul metrics: - accuracy - bleu --- # Aya-101-GGUF This repo contains GGUF format model files for Cohere's [Aya-101](https://huggingface.co/CohereForAI/aya-101) model Quantized using Huggingface's [candle](https://github.com/huggingface/candle) framework ## How to use with Candle's quantized T5 example Visit the [candle T5 example](https://github.com/huggingface/candle/tree/main/candle-examples/examples/quantized-t5) for more detailed instruction 1. Clone candle repo: ```bash git clone https://github.com/huggingface/candle.git cd candle/candle-examples ``` 2. Run the following command: ```bash cargo run --example quantized-t5 --release -- \ --model-id "kcoopermiller/aya-101-GGUF" \ --weight-file "aya-101.Q2_K.gguf" \ --config-file "config.json" \ --prompt "भारत में इतनी सारी भाषाएँ क्यों हैं?" \ --temperature 0 ``` Available weight files: - aya-101.Q2_K.gguf - aya-101.Q3_K.gguf - aya-101.Q4_0.gguf - aya-101.Q4_1.gguf - aya-101.Q4_K.gguf - aya-101.Q5_0.gguf - aya-101.Q5_1.gguf - aya-101.Q5_K.gguf - aya-101.Q6_K.gguf - aya-101.Q8_0.gguf - aya-101.Q8_1.gguf (not supported on candle yet) - aya-101.Q8_K.gguf (not supported on candle yet)