Model reference · open weights
LLaMmlein2Vec is an open-weight embedding model from LSX-UniWue. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Released by | LSX-UniWue |
|---|---|
| Type | Embedding models |
| Task | Embeddings |
| Parameters (lead) | 100M |
| Context | 8k tokens |
| Runs with | llm2vec |
| Based on | LSX-UniWue/LLaMmlein_120M |
| Released | 2025-07-14 |
| Popularity | 527 downloads / month |
| Licence | Commercial licence needed |
About
LLäMmlein2Vec 120M is a German encoder language model derived from our German decoder-only model LLäMmlein 120M via LLM2Vec.
We provide three transformed models:
LLäMmlein2Vec 120M ← You are here
Find more details in our preprint!
You can use LLäMmlein2Vec with the llm2vec library.
import torch
from llm2vec import LLM2Vec
model_id = "LSX-UniWue/LLaMmlein2Vec_120M"
l2v = LLM2Vec.from_pretrained(
model_id,
device_map="cuda" if torch.cuda.is_available() else "cpu",
torch_dtype=torch.bfloat16,
)
We release the ModernGBERT models under a research-only RAIL-M license. See license.md for details. Data Take Down
From the published model card. Full card on the HuggingFace links in the sidebar.
Using it via the API
Once AxForge deploys llammlein2vec for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (llammlein2vec below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/embeddings \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"llammlein2vec","input":"text to embed"}'
Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.