Optimization of all our open-source models to be used even with a smartphone
Optimization of all our open-source models to be used even with a smartphone
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September 1, 2023
On July 5th, we introduced our first Language Model (LLM) fully tailored in Spanish. This new product, called LINCE, employs innovative efficient training techniques in LLMs (fine-tuning).
LINCE, designed with an instructional approach, offers great versatility as it can be used through API and Clibrain's native applications: Clichat, Clibot, and Clicall. This uniqueness allows companies of all sizes and industries to implement Artificial Intelligence in Spanish, ensuring their security and privacy while obtaining optimal results ready for production use.
Furthermore, during the months of July and August 2023, we made adaptations of Llama 2 in its 7B and 13B versions for instruction tracking in Spanish. This work demonstrates our firm commitment to the Spanish-speaking community, offering solutions in record time that go beyond the simple development of language models.
Currently, our next step is to optimize LINCE to make it accessible on lower-capacity devices. This advancement will allow any user to make inferences or train a model from home, without the need for a significant monetary investment.
Quantized models facilitate installation and operation on more affordable devices such as servers, laptops, or mobile devices, thereby eliminating the need for an internet connection. This enables usage in situations where the device lacks a reliable internet connection, whether for security reasons or due to location factors.
The process to make this model more efficient is called
On July 5th, we introduced our first Language Model (LLM) fully tailored in Spanish. This new product, called LINCE, employs innovative efficient training techniques in LLMs (fine-tuning).
LINCE, designed with an instructional approach, offers great versatility as it can be used through API and Clibrain's native applications: Clichat, Clibot, and Clicall. This uniqueness allows companies of all sizes and industries to implement Artificial Intelligence in Spanish, ensuring their security and privacy while obtaining optimal results ready for production use.
Furthermore, during the months of July and August 2023, we made adaptations of Llama 2 in its 7B and 13B versions for instruction tracking in Spanish. This work demonstrates our firm commitment to the Spanish-speaking community, offering solutions in record time that go beyond the simple development of language models.
Currently, our next step is to optimize LINCE to make it accessible on lower-capacity devices. This advancement will allow any user to make inferences or train a model from home, without the need for a significant monetary investment.
Quantized models facilitate installation and operation on more affordable devices such as servers, laptops, or mobile devices, thereby eliminating the need for an internet connection. This enables usage in situations where the device lacks a reliable internet connection, whether for security reasons or due to location factors.
The process to make this model more efficient is called
On July 5th, we introduced our first Language Model (LLM) fully tailored in Spanish. This new product, called LINCE, employs innovative efficient training techniques in LLMs (fine-tuning).
LINCE, designed with an instructional approach, offers great versatility as it can be used through API and Clibrain's native applications: Clichat, Clibot, and Clicall. This uniqueness allows companies of all sizes and industries to implement Artificial Intelligence in Spanish, ensuring their security and privacy while obtaining optimal results ready for production use.
Furthermore, during the months of July and August 2023, we made adaptations of Llama 2 in its 7B and 13B versions for instruction tracking in Spanish. This work demonstrates our firm commitment to the Spanish-speaking community, offering solutions in record time that go beyond the simple development of language models.
Currently, our next step is to optimize LINCE to make it accessible on lower-capacity devices. This advancement will allow any user to make inferences or train a model from home, without the need for a significant monetary investment.
Quantized models facilitate installation and operation on more affordable devices such as servers, laptops, or mobile devices, thereby eliminating the need for an internet connection. This enables usage in situations where the device lacks a reliable internet connection, whether for security reasons or due to location factors.
The process to make this model more efficient is called
On July 5th, we introduced our first Language Model (LLM) fully tailored in Spanish. This new product, called LINCE, employs innovative efficient training techniques in LLMs (fine-tuning).
LINCE, designed with an instructional approach, offers great versatility as it can be used through API and Clibrain's native applications: Clichat, Clibot, and Clicall. This uniqueness allows companies of all sizes and industries to implement Artificial Intelligence in Spanish, ensuring their security and privacy while obtaining optimal results ready for production use.
Furthermore, during the months of July and August 2023, we made adaptations of Llama 2 in its 7B and 13B versions for instruction tracking in Spanish. This work demonstrates our firm commitment to the Spanish-speaking community, offering solutions in record time that go beyond the simple development of language models.
Currently, our next step is to optimize LINCE to make it accessible on lower-capacity devices. This advancement will allow any user to make inferences or train a model from home, without the need for a significant monetary investment.
Quantized models facilitate installation and operation on more affordable devices such as servers, laptops, or mobile devices, thereby eliminating the need for an internet connection. This enables usage in situations where the device lacks a reliable internet connection, whether for security reasons or due to location factors.
The process to make this model more efficient is called