Quantization made by Richard Erkhov.
Occiglot-7B-ES-EN is a generative language model with 7B parameters for Spanish and English and trained by the
Occiglot Research Collective.
It is based on
Mistral-7B-v0.1 and trained on 112B tokens of additional multilingual and code data with a block size of 8,192 tokens per sample.
Note that the model is a general-purpose base model and was not instruction-fine-tuned nor optimized for chat or other applications. We make an instruction tuned variant available as
occiglot-7b-es-en-instruct
This is the first release of an ongoing open research project for multilingual language models.
If you want to train a model for your own language or are working on evaluations, please contact us or join our
Discord server.
We are open for collaborations!You can use this model directly with a pipeline for text generation. Since the generation relies on some randomness, we
set a seed for reproducibility:
1>>> from transformers import pipeline, set_seed
2>>> generator = pipeline('text-generation', model='occiglot/occiglot-7b-es-en')
3>>> set_seed(42)
4>>> generator("Hola, soy una modelo lingüística", max_length=40, num_return_sequences=1)
5[{'generated_text': 'Hola, soy una modelo lingüística que puede ayudarte a traducir textos entre español e inglés. Si me envías un texto en español'}]
The training data is the respective subset of the data used for
occiglot-7b-eu5, i.e. Spanish plus English and Code.
The training data was prepared using
lm-datasets.
The exact data configuration is
here.
Tokenizer is unchanged from
Mistral-7B-v0.1.
Preliminary evaluation results can be found below.
Please note that the non-English results are based on partially machine-translated datasets and English prompts (
Belebele and
Okapi framework) and thus should be interpreted with caution, e.g., biased towards English model performance.
Currently, we are working on more suitable benchmarks for Spanish, French, German, and Italian.
