C4AI Aya Expanse
Collection
Aya Expanse is an open-weight research release of a model with highly advanced multilingual capabilities.
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Model Card for Aya-Expanse-32B
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 of models with the result of a year’s dedicated research from Cohere For AI, including data arbitrage, multilingual preference training, safety tuning, and model merging. 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.
- Developed by: Cohere For AI
- Point of Contact: Cohere For AI: cohere.for.ai
- License: CC-BY-NC, requires also adhering to C4AI's 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 or our Hugging Face Space for interactive exploration.
How to Use Aya Expanse
Install the transformers library and load Aya Expanse 32B as follows:
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")
## <BOS_TOKEN><|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:
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:
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 32B against Gemma 2 27B, Llama 3.1 70B, Mixtral 8x22B, and Qwen 2.5 35B using the dolly_human_edited subset from the Aya Evaluation Suite dataset and m-ArenaHard, a dataset based on the Arena-Hard-Auto dataset and translated to the 23 languages we support in Aya Expanse. 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.
Model Card Contact
For errors or additional questions about details in this model card, contact [email protected].
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 License with an acceptable use addendum, and also requires adhering to C4AI's Acceptable Use Policy.
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