Comparar
Blip2 Opt 2.7B vs Blip2 Flan T5 Xl
Ponga de dos a cuatro modelos lado a lado según los campos que deciden un despliegue: contexto, precio, región, licencia, idiomas, alojamiento y qué está verificado.
| Blip2 Opt 2.7B | Blip2 Flan T5 Xl | |
|---|---|---|
| Proveedor | Salesforce | Salesforce |
| Parámetros | 3.7B | 3.9B |
| Ventana de contexto | Sin verificar: el proveedor no ha documentado esta afirmación. | Sin verificar: el proveedor no ha documentado esta afirmación. |
| Licencia | mit | mit |
| Modalidades | text, vision | text, vision |
| Fecha de publicación | 06 feb 2023 | 06 feb 2023 |
| Idiomas | Sólido: en Adecuado: — | Sólido: en Adecuado: — |
| Pesos abiertos | sí | sí |
| Tareas | Visión, Bajo coste | Visión |
Cuando dos modelos difieren, esta tabla muestra la diferencia y se detiene. LLM EU no publica ninguna insignia de ganador sin una puntuación documentada para esa tarea, y una cifra faltante sigue faltando en lugar de convertirse en un cero.
Cuándo usarlo
Blip2 Opt 2.7B
Puntos fuertes
- open weights are published on Hugging Face and can be downloaded without a vendor agreement
- mit licence, so commercial self-hosting is permitted without a separate agreement
- at 3.7B parameters it fits on a single accelerator
- the model page lists en
Límites
- catalogue only — LLM EU does not run this model, and nothing on this card implies an LLM EU endpoint
- no evaluation has been run by LLM EU
- the published configuration records no context window, so the card carries none
- at 3.7B parameters, the weights fit on a single modest accelerator
- vision checkpoints are heavier to serve than their parameter count alone suggests, because the image encoder and pre-processing run alongside the language model
Tareas
Blip2 Flan T5 Xl
Puntos fuertes
- open weights are published on Hugging Face and can be downloaded without a vendor agreement
- mit licence, so commercial self-hosting is permitted without a separate agreement
- at 3.9B parameters it fits on a single accelerator
- the model page lists en
Límites
- catalogue only — LLM EU does not run this model, and nothing on this card implies an LLM EU endpoint
- no evaluation has been run by LLM EU
- the published configuration records no context window, so the card carries none
- at 3.9B parameters, the weights fit on a single modest accelerator
- vision checkpoints are heavier to serve than their parameter count alone suggests, because the image encoder and pre-processing run alongside the language model
Tareas
Tareas: Visión