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
extra_gated_prompt: >-
By submitting this form, you agree to the [License
Agreement](https://cohere.com/c4ai-cc-by-nc-license) and acknowledge that the
information you provide will be collected, used, and shared in accordance with
Cohere’s [Privacy Policy]( https://cohere.com/privacy). You’ll receive email
updates about Cohere Labs and Cohere research, events, products and services.
You can unsubscribe at any time.
extra_gated_fields:
Name: text
Affiliation: text
Country: country
I agree to use this model for non-commercial use ONLY: checkbox
base_model:
- CohereLabs/c4ai-command-a-03-2025
widget:
- text: >-
Translate everything that follows into Spanish:
Enterprises rely on translation for some of their most sensitive and
business-critical documents and cannot risk data leakage, compliance
violations, or misunderstandings. Mistranslated documents can reduce trust
and have strategic implications.
example_title: Example 1
- text: >-
Take the English text that follows and translate it into German. Only
respond with the translated text.
Command A Translate is available today on the Cohere platform and for
research use on Hugging Face. If you are interested in private or on-prem
deployments, please contact our sales team for bespoke pricing.
example_title: Example 2
- text: >-
Can you rewrite that in French please?
To meet the needs of global enterprises, the model supports translation
across 23 widely used business languages: English, French, Spanish,
Italian, German, Portuguese, Japanese, Korean, Arabic, Chinese, Russian,
Polish, Turkish, Vietnamese, Dutch, Czech, Indonesian, Ukrainian,
Romanian, Greek, Hindi, Hebrew, and Persian.
example_title: Example 3
Model Card for Cohere Labs Command A Translate
Model Summary
Cohere Labs Command A Translate is an open weights research release of a 111 billion parameter model that achieves state-of-the-art performance on translation quality.
Developed by: Cohere and Cohere Labs
- Point of Contact: Cohere For AI: Cohere Labs
- License: CC-BY-NC, requires also adhering to Cohere Lab's Acceptable Use Policy
- Model: command-a-translate-08-2025
- Model Size: 111B
- Context length: 8k input, 8k output
For more details about this model, please check out our blog post.
Try Cohere Labs Command A Translate
You can try out Cohere Labs Command A Translate before downloading the weights in our hosted Hugging Face Space.
Usage
Please install transformers from the source repository that includes the necessary changes for this model.
# pip install transformers
from transformers import AutoTokenizer, AutoModelForCausalLM
model_id = "CohereLabs/command-a-translate-08-2025"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)
# Format message with the command-a-translate-08-2025 chat template
messages = [{"role": "user", "content": "Translate everything that follows into Spanish:\n\n 'Enterprises rely on translation for some of their most sensitive and business-critical documents and cannot risk data leakage, compliance violations, or misunderstandings. Mistranslated documents can reduce trust and have strategic implications.'"}]
input_ids = tokenizer.apply_chat_template(
messages,
tokenize=True,
add_generation_prompt=True,
return_tensors="pt"
)
gen_tokens = model.generate(
input_ids,
max_new_tokens=4096,
do_sample=True,
temperature=0.3,
)
gen_text = tokenizer.decode(gen_tokens[0])
print(gen_text)
You can also use the model directly using transformers pipeline abstraction:
from transformers import AutoTokenizer, pipeline
import torch
model_id = "CohereLabs/command-a-translate-08-2025"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "Translate everything that follows into Spanish:\n\n 'Enterprises rely on translation for some of their most sensitive and business-critical documents and cannot risk data leakage, compliance violations, or misunderstandings. Mistranslated documents can reduce trust and have strategic implications.'"},
]
tokenizer = AutoTokenizer.from_pretrained(model_id)
text = tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True,
)
outputs = pipe(
messages,
max_new_tokens=300,
)
print(outputs[0]["generated_text"][-1])
Model Details
Input: Text only.
Output: Model generates text.
Model Architecture: This is an auto-regressive language model that uses an optimized transformer architecture. After pretraining, this model uses supervised fine-tuning (SFT) and preference training to align model behavior to human preferences for helpfulness and safety. The model features three layers with sliding window attention (window size 4096) and RoPE for efficient local context modeling and relative positional encoding. A fourth layer uses global attention without positional embeddings, enabling unrestricted token interactions across the entire sequence.
Languages covered: The model has been trained on 23 languages: English, French, Spanish, Italian, German, Portuguese, Japanese, Korean, Arabic, Chinese, Russian, Polish, Turkish, Vietnamese, Dutch, Czech, Indonesian, Ukrainian, Romanian, Greek, Hindi, Hebrew, and Persian.
Context Length: Command A Translate supports a context length of 8K input & 8K output length.
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 111 billion parameter model to researchers all over the world. This model is governed by a CC-BY-NC License (Non-Commercial) with an acceptable use addendum, and also requires adhering to Cohere Lab's Acceptable Use Policy. If you are interested in commercial use, please contact Cohere’s Sales team.
Try it now:
You can try Command A Translate in the playground here. You can also use it in our dedicated Hugging Face Space here.