Model reference · open weights

hubert

Available as managed deployment Embeddings bosonai Embeddings 1 variants 38k dl/mo

hubert is an open-weight embedding model from bosonai. 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 bybosonai
TypeEmbedding models
TaskEmbeddings
Parameters (lead)94M
Runs withtransformers
Released2025-07-19
Popularity38k downloads / month
LicenceOpen weights

About

What hubert is

A general-purpose HuBERT-Base checkpoint released by Boson AI, used inside the Higgs Audio Tokenizer as the semantic teacher.

Read the full model card

What it is

  • Standard HuBERT-Base architecture (12 transformer layers, hidden size 768, ~95M params)
  • 16 kHz audio input
  • Loadable via AutoModel with trust_remote_code=True
  • Outputs 768-dim per-layer hidden states (output_hidden_states=True)

How it is used in Higgs Audio

The Higgs Audio Tokenizer distills semantic features from this HuBERT into its semantic branch. From boson_multimodal/audio_processing/higgs_audio_tokenizer.py (semantic_techer="hubert_base_general"):

from transformers import AutoModel

semantic_model = AutoModel.from_pretrained("bosonai/hubert_base", trust_remote_code=True)
# 16 kHz, 768-dim semantic features, all hidden layers consumed by the tokenizer

Direct usage

import torch
import torchaudio
from transformers import AutoModel

model = AutoModel.from_pretrained("bosonai/hubert_base", trust_remote_code=True).eval()

waveform, sr = torchaudio.load("audio.wav")
if sr != 16000:
    waveform = torchaudio.functional.resample(waveform, sr, 16000)

with torch.no_grad():
    out = model(waveform, output_hidden_states=True)

# out.last_hidden_state:  (B, T, 768)
# out.hidden_states:      tuple of (B, T, 768) for each of the 13 layers (embedding + 12 transformer blocks)

License

Apache 2.0.

From the published model card. Full card on the HuggingFace links in the sidebar.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys hubert for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (hubert 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":"hubert","input":"text to embed"}'

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