finetuned_mixedbread_ai_deepset_mxbai_embed_de_large_v1
Released by FareedKhan in 2024, finetuned_mixedbread_ai_deepset_mxbai_embed_de_large_v1 is an embedding model. finetuned_mixedbread_ai_deepset_mxbai_embed_de_large_v1 is an open-weights embed model.
by FareedKhan
Best for
Ways to use finetuned_mixedbread_ai_deepset_mxbai_embed_de_large_v1 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your FareedKhan API key. osFoundry discovers finetuned_mixedbread_ai_deepset_mxbai_embed_de_large_v1 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
finetuned_mixedbread_ai_deepset_mxbai_embed_de_large_v1 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.
finetuned_mixedbread_ai_deepset_mxbai_embed_de_large_v1 vs similar models
| Model | Org | Params | Context | Input price | Self-host |
|---|
| finetuned_mixedbread_ai_deepset_mxbai_embed_de_large_v1 | FareedKhan | — | — | Free (local) | Yes |
| japanese-wav2vec2-base | reazon-research | — | — | Free (local) | Yes |
| AIT-86M-GGUF | augmem | — | — | Free (local) | Yes |
| moe-girl-v2 | johnyy212 | — | — | Free (local) | Yes |
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about finetuned_mixedbread_ai_deepset_mxbai_embed_de_large_v1
Is finetuned_mixedbread_ai_deepset_mxbai_embed_de_large_v1 free to use?
finetuned_mixedbread_ai_deepset_mxbai_embed_de_large_v1 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 finetuned_mixedbread_ai_deepset_mxbai_embed_de_large_v1 commercially?
Commercial use is allowed with conditions. Licence terms not specified — verify the upstream model card before commercial use. Check upstream documentation.
Can I run finetuned_mixedbread_ai_deepset_mxbai_embed_de_large_v1 locally?
Yes. finetuned_mixedbread_ai_deepset_mxbai_embed_de_large_v1 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is finetuned_mixedbread_ai_deepset_mxbai_embed_de_large_v1 best at?
finetuned_mixedbread_ai_deepset_mxbai_embed_de_large_v1 is well-suited to sentence similarity.
How do I use finetuned_mixedbread_ai_deepset_mxbai_embed_de_large_v1 in osFoundry?
Paste your FareedKhan API key in the key dialog (or deploy the open weights for self-hostable models), assign finetuned_mixedbread_ai_deepset_mxbai_embed_de_large_v1 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by FareedKhan on November 13, 2024. Source: https://huggingface.co/FareedKhan/finetuned_mixedbread_ai_deepset_mxbai_embed_de_large_v1