Quantization made by Richard Erkhov. [Github](https://github.com/RichardErkhov) [Discord](https://discord.gg/pvy7H8DZMG) [Request more models](https://github.com/RichardErkhov/quant_request) aya-expanse-32b-ungated - GGUF - Model creator: https://huggingface.co/adamo1139/ - Original model: https://huggingface.co/adamo1139/aya-expanse-32b-ungated/ | Name | Quant method | Size | | ---- | ---- | ---- | | [aya-expanse-32b-ungated.Q2_K.gguf](https://huggingface.co/RichardErkhov/adamo1139_-_aya-expanse-32b-ungated-gguf/blob/main/aya-expanse-32b-ungated.Q2_K.gguf) | Q2_K | 11.93GB | | [aya-expanse-32b-ungated.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/adamo1139_-_aya-expanse-32b-ungated-gguf/blob/main/aya-expanse-32b-ungated.Q3_K_S.gguf) | Q3_K_S | 13.7GB | | [aya-expanse-32b-ungated.Q3_K.gguf](https://huggingface.co/RichardErkhov/adamo1139_-_aya-expanse-32b-ungated-gguf/blob/main/aya-expanse-32b-ungated.Q3_K.gguf) | Q3_K | 15.12GB | | [aya-expanse-32b-ungated.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/adamo1139_-_aya-expanse-32b-ungated-gguf/blob/main/aya-expanse-32b-ungated.Q3_K_M.gguf) | Q3_K_M | 15.12GB | | [aya-expanse-32b-ungated.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/adamo1139_-_aya-expanse-32b-ungated-gguf/blob/main/aya-expanse-32b-ungated.Q3_K_L.gguf) | Q3_K_L | 16.36GB | | [aya-expanse-32b-ungated.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/adamo1139_-_aya-expanse-32b-ungated-gguf/blob/main/aya-expanse-32b-ungated.IQ4_XS.gguf) | IQ4_XS | 16.75GB | | [aya-expanse-32b-ungated.Q4_0.gguf](https://huggingface.co/RichardErkhov/adamo1139_-_aya-expanse-32b-ungated-gguf/blob/main/aya-expanse-32b-ungated.Q4_0.gguf) | Q4_0 | 17.43GB | | [aya-expanse-32b-ungated.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/adamo1139_-_aya-expanse-32b-ungated-gguf/blob/main/aya-expanse-32b-ungated.IQ4_NL.gguf) | IQ4_NL | 17.59GB | | [aya-expanse-32b-ungated.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/adamo1139_-_aya-expanse-32b-ungated-gguf/blob/main/aya-expanse-32b-ungated.Q4_K_S.gguf) | Q4_K_S | 17.55GB | | [aya-expanse-32b-ungated.Q4_K.gguf](https://huggingface.co/RichardErkhov/adamo1139_-_aya-expanse-32b-ungated-gguf/blob/main/aya-expanse-32b-ungated.Q4_K.gguf) | Q4_K | 18.44GB | | [aya-expanse-32b-ungated.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/adamo1139_-_aya-expanse-32b-ungated-gguf/blob/main/aya-expanse-32b-ungated.Q4_K_M.gguf) | Q4_K_M | 18.44GB | | [aya-expanse-32b-ungated.Q4_1.gguf](https://huggingface.co/RichardErkhov/adamo1139_-_aya-expanse-32b-ungated-gguf/blob/main/aya-expanse-32b-ungated.Q4_1.gguf) | Q4_1 | 19.19GB | | [aya-expanse-32b-ungated.Q5_0.gguf](https://huggingface.co/RichardErkhov/adamo1139_-_aya-expanse-32b-ungated-gguf/blob/main/aya-expanse-32b-ungated.Q5_0.gguf) | Q5_0 | 20.95GB | | [aya-expanse-32b-ungated.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/adamo1139_-_aya-expanse-32b-ungated-gguf/blob/main/aya-expanse-32b-ungated.Q5_K_S.gguf) | Q5_K_S | 20.95GB | | [aya-expanse-32b-ungated.Q5_K.gguf](https://huggingface.co/RichardErkhov/adamo1139_-_aya-expanse-32b-ungated-gguf/blob/main/aya-expanse-32b-ungated.Q5_K.gguf) | Q5_K | 21.47GB | | [aya-expanse-32b-ungated.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/adamo1139_-_aya-expanse-32b-ungated-gguf/blob/main/aya-expanse-32b-ungated.Q5_K_M.gguf) | Q5_K_M | 21.47GB | | [aya-expanse-32b-ungated.Q5_1.gguf](https://huggingface.co/RichardErkhov/adamo1139_-_aya-expanse-32b-ungated-gguf/blob/main/aya-expanse-32b-ungated.Q5_1.gguf) | Q5_1 | 22.71GB | | [aya-expanse-32b-ungated.Q6_K.gguf](https://huggingface.co/RichardErkhov/adamo1139_-_aya-expanse-32b-ungated-gguf/blob/main/aya-expanse-32b-ungated.Q6_K.gguf) | Q6_K | 24.68GB | | [aya-expanse-32b-ungated.Q8_0.gguf](https://huggingface.co/RichardErkhov/adamo1139_-_aya-expanse-32b-ungated-gguf/blob/main/aya-expanse-32b-ungated.Q8_0.gguf) | Q8_0 | 31.97GB | Original model description: --- inference: false library_name: transformers language: - en - fr - de - es - it - pt - ja - ko - zh - ar - el - fa - pl - id - cs - he - hi - nl - ro - ru - tr - uk - vi license: cc-by-nc-4.0 --- # Model Card for Aya-Expanse-32B Ungated Aya-Expanse 32B, but not gated! **Aya Expanse 32B** is an open-weight research release of a model with highly advanced multilingual capabilities. It focuses on pairing a highly performant pre-trained [Command family](https://huggingface.co/CohereForAI/c4ai-command-r-plus) of models with the result of a year’s dedicated research from [Cohere For AI](https://cohere.for.ai/), including [data arbitrage](https://arxiv.org/pdf/2408.14960), [multilingual preference training](https://arxiv.org/abs/2407.02552), [safety tuning](https://arxiv.org/abs/2406.18682), and [model merging](https://arxiv.org/abs/2410.10801). The result is a powerful multilingual large language model serving 23 languages. This model card corresponds to the 32-billion version of the Aya Expanse model. We also released an 8-billion version which you can find [here](https://huggingface.co/CohereForAI/aya-expanse-8B). - Developed by: [Cohere For AI](https://cohere.for.ai/) - Point of Contact: Cohere For AI: [cohere.for.ai](https://cohere.for.ai/) - License: [CC-BY-NC](https://cohere.com/c4ai-cc-by-nc-license), requires also adhering to [C4AI's Acceptable Use Policy](https://docs.cohere.com/docs/c4ai-acceptable-use-policy) - Model: Aya Expanse 32B - Model Size: 32 billion parameters ### Supported Languages We cover 23 languages: Arabic, Chinese (simplified & traditional), Czech, Dutch, English, French, German, Greek, Hebrew, Hebrew, Hindi, Indonesian, Italian, Japanese, Korean, Persian, Polish, Portuguese, Romanian, Russian, Spanish, Turkish, Ukrainian, and Vietnamese. ### Try it: Aya Expanse in Action Use the [Cohere playground](https://dashboard.cohere.com/playground/chat) or our [Hugging Face Space](https://huggingface.co/spaces/CohereForAI/aya_expanse) for interactive exploration. ### How to Use Aya Expanse Install the transformers library and load Aya Expanse 32B as follows: ```python from transformers import AutoTokenizer, AutoModelForCausalLM model_id = "CohereForAI/aya-expanse-32b" tokenizer = AutoTokenizer.from_pretrained(model_id) model = AutoModelForCausalLM.from_pretrained(model_id) # Format message with the chat template messages = [{"role": "user", "content": "Anneme onu ne kadar sevdiğimi anlatan bir mektup yaz"}] input_ids = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt") ## <|START_OF_TURN_TOKEN|><|USER_TOKEN|>Anneme onu ne kadar sevdiğimi anlatan bir mektup yaz<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|> gen_tokens = model.generate( input_ids, max_new_tokens=100, do_sample=True, temperature=0.3, ) gen_text = tokenizer.decode(gen_tokens[0]) print(gen_text) ``` ### Example Notebooks **Fine-Tuning:** - [Detailed Fine-Tuning Notebook](https://colab.research.google.com/drive/1ryPYXzqb7oIn2fchMLdCNSIH5KfyEtv4). **Community-Contributed Use Cases:**: The following notebooks contributed by *Cohere For AI Community* members show how Aya Expanse can be used for different use cases: - [Mulitlingual Writing Assistant](https://colab.research.google.com/drive/1SRLWQ0HdYN_NbRMVVUHTDXb-LSMZWF60) - [AyaMCooking](https://colab.research.google.com/drive/1-cnn4LXYoZ4ARBpnsjQM3sU7egOL_fLB?usp=sharing) - [Multilingual Question-Answering System](https://colab.research.google.com/drive/1bbB8hzyzCJbfMVjsZPeh4yNEALJFGNQy?usp=sharing) ## Model Details **Input**: Models input text only. **Output**: Models generate text only. **Model Architecture**: Aya Expanse 32B is an auto-regressive language model that uses an optimized transformer architecture. Post-training includes supervised finetuning, preference training, and model merging. **Languages covered**: The model is particularly optimized for multilinguality and supports the following languages: Arabic, Chinese (simplified & traditional), Czech, Dutch, English, French, German, Greek, Hebrew, Hindi, Indonesian, Italian, Japanese, Korean, Persian, Polish, Portuguese, Romanian, Russian, Spanish, Turkish, Ukrainian, and Vietnamese **Context length**: 128K ### Evaluation We evaluated Aya Expanse 8B against Gemma 2 9B, Llama 3.1 8B, Ministral 8B, and Qwen 2.5 7B using m-ArenaHard, a dataset based on the [Arena-Hard-Auto dataset](https://huggingface.co/datasets/lmarena-ai/arena-hard-auto-v0.1) and translated to the 23 languages we support in Aya Expanse 8B. Win-rates were determined using gpt-4o-2024-08-06 as a judge. For a conservative benchmark, we report results from gpt-4o-2024-08-06, though gpt-4o-mini scores showed even stronger performance. The m-ArenaHard dataset, used to evaluate Aya Expanse’s capabilities, is publicly available [here](https://huggingface.co/datasets/CohereForAI/m-ArenaHard). ### Model Card Contact For errors or additional questions about details in this model card, contact info@for.ai. ### Terms of Use We hope that the release of this model will make community-based research efforts more accessible, by releasing the weights of a highly performant multilingual model to researchers all over the world. This model is governed by a [CC-BY-NC](https://cohere.com/c4ai-cc-by-nc-license) License with an acceptable use addendum, and also requires adhering to [C4AI's Acceptable Use Policy](https://docs.cohere.com/docs/c4ai-acceptable-use-policy).