Modelos

8 modelos

Llama Guard 4 is a Llama 4 Scout-derived multimodal pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content in both LLM...

por meta-llama30 abr 2025163,84 mil de contexto316 KRW / 316 KRW · 1M

Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward...

por meta-llama6 abr 20251,05 M de contexto351 KRW / 1221 KRW · 1M

Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input...

por meta-llama6 abr 20251,31 M de contexto176 KRW / 527 KRW · 1M

The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...

por meta-llama7 dic 2024131,07 mil de contexto176 KRW / 562 KRW · 1M

Llama 3.2 1B is a 1-billion-parameter language model focused on efficiently performing natural language tasks, such as summarization, dialogue, and multilingual text analysis. Its smaller size allows it to operate...

por meta-llama25 sept 202460 mil de contexto47 KRW / 353 KRW · 1M

Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization. Designed with the latest transformer architecture, it...

por meta-llama25 sept 2024131,07 mil de contexto88 KRW / 579 KRW · 1M

Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 70B instruct-tuned version is optimized for high quality dialogue usecases. It has demonstrated strong...

por meta-llama23 jul 2024131,07 mil de contexto702 KRW / 702 KRW · 1M

Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient. It has demonstrated strong performance compared to...

por meta-llama23 jul 2024131,07 mil de contexto88 KRW / 140 KRW · 1M