Downloads · 30 days
32
52% of all-time downloads
Emomni-v1-bnb-4bit
Jotakak/Emomni-v1-bnb-4bit
Emomni-v1-bnb-4bit is a machine learning model from Jotakak. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Complete checkpoint with global LoRA already merged, followed by bitsandbytes NF4 quantization with double quantization and BF16 compute. No separate adapter is required. lmhead is excluded from quantization; existing…
All-time downloads
61
Public
Parameters
8.3B
6.1 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors6 GB · 100%
Parameter types
How the weights are stored.
U87.2B · 86%
Base models
Model card
From the Hugging Face model README
Emomni-v1 Base — NF4
Complete checkpoint with global LoRA already merged, followed by bitsandbytes
NF4 quantization with double quantization and BF16 compute. No separate adapter
is required. lm_head is excluded from quantization; existing quantization
coverage of the other components is preserved.
Corresponding merged BF16 checkpoint.
The existing quantized weights are retained: recomputing NF4 from the matching merged BF16 checkpoint verified all 2,792 serialized tensors as identical.
Use the Emomni-v1 code:
bash scripts/run_serve.sh --model Jotakak/Emomni-v1-bnb-4bit
The custom model is loaded by src.modeling_emomni.EmomniModel, rather than
the generic AutoModelForCausalLM loader. Local text/audio loading and generation
were checked. These checks are not a new quality benchmark.
- Type
- emomni-v1
- License
- apache-2.0
- Created
- Mar 4, 2026
- Updated
- Oct 11, 2026