Agente-GPT-Qwen-2.5-7B-Spanish_English_GGUF_q6_k
Released by Agnuxo in 2024, Agente-GPT-Qwen-2.5-7B-Spanish_English_GGUF_q6_k is a 7 billion parameter chat model. Agente-GPT-Qwen-2.5-7B-Spanish_English_GGUF_q6_k is an open-weights chat model with roughly 7 billion parameters.
by Agnuxo · 7B parameters
Best for
Ways to use Agente-GPT-Qwen-2.5-7B-Spanish_English_GGUF_q6_k in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your Agnuxo API key. osFoundry discovers Agente-GPT-Qwen-2.5-7B-Spanish_English_GGUF_q6_k automatically — assign it to a Maestro role (router, direct, orchestrator, or fallback) in the Pipeline tab and it is live in every chat. Your key, your provider account — no token markup.
Deploy a dedicated endpoint
Agente-GPT-Qwen-2.5-7B-Spanish_English_GGUF_q6_k is open-weights — run it locally for free, or deploy a dedicated GPU endpoint in your workspace for reserved capacity with no rate limits.
Use it in a Room App
Room Apps declare AI features in their manifest, then call them with invokeAI:
import { invokeAI } from '@osfoundry/app-sdk'
// 'summarize' is an AI feature declared in your app manifest.
const result = await invokeAI('summarize', userText)
Call it from your own apps
Once a model is wired into your workspace you can host it as an API and reach it from your own services, scripts, or CI — outside osFoundry.
What hardware can run Agente-GPT-Qwen-2.5-7B-Spanish_English_GGUF_q6_k
Agente-GPT-Qwen-2.5-7B-Spanish_English_GGUF_q6_k runs on a single 16GB consumer GPU (~5 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~17 GB).
Agente-GPT-Qwen-2.5-7B-Spanish_English_GGUF_q6_k vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Agente-GPT-Qwen-2.5-7B-Spanish_English_GGUF_q6_k
Is Agente-GPT-Qwen-2.5-7B-Spanish_English_GGUF_q6_k free to use?
Agente-GPT-Qwen-2.5-7B-Spanish_English_GGUF_q6_k is free to run locally on your own hardware. Hosted access through osFoundry is metered (input Free (local), output Free (local)). You can switch between local and hosted at any time.
Can I use Agente-GPT-Qwen-2.5-7B-Spanish_English_GGUF_q6_k commercially?
Commercial use is allowed with conditions. Licence terms not specified — verify the upstream model card before commercial use. Check upstream documentation.
How much VRAM does Agente-GPT-Qwen-2.5-7B-Spanish_English_GGUF_q6_k need?
Approximately 5 GB at Q4 quantisation, or 17 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Agente-GPT-Qwen-2.5-7B-Spanish_English_GGUF_q6_k locally?
Yes. Agente-GPT-Qwen-2.5-7B-Spanish_English_GGUF_q6_k is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Agente-GPT-Qwen-2.5-7B-Spanish_English_GGUF_q6_k best at?
Agente-GPT-Qwen-2.5-7B-Spanish_English_GGUF_q6_k is well-suited to text generation.
How do I use Agente-GPT-Qwen-2.5-7B-Spanish_English_GGUF_q6_k in osFoundry?
Paste your Agnuxo API key in the key dialog (or deploy the open weights for self-hostable models), assign Agente-GPT-Qwen-2.5-7B-Spanish_English_GGUF_q6_k to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by Agnuxo on September 19, 2024. Source: https://huggingface.co/Agnuxo/Agente-GPT-Qwen-2.5-7B-Spanish_English_GGUF_q6_k