Splade_PP_en_v1-mlx

MLX (bfloat16) conversion of prithivida/Splade_PP_en_v1 for Apple Silicon, produced by NomaDamas/SPLADE-mlx.

Independent Apache-2.0 SPLADE++ reproduction (BERT-base), freely usable commercially.

Changes from upstream: PyTorch checkpoint converted to MLX safetensors (parameter re-mapping, cast to bfloat16). No training or fine-tuning was performed.

Quality: Separate fp32 conversion validation: max |logit delta| 5.5e-05, sparse cosine 1.000000, top-64 term overlap 100%. This repository stores bfloat16 weights. Any fp32 parity number above comes from a separate fp32 conversion of the upstream checkpoint, not this linked bfloat16 artifact. Full methodology: see the SPLADE-mlx report.

Usage

from splade_mlx import load
import mlx.core as mx

model, tok = load("NomaDamas/Splade_PP_en_v1-mlx")
enc = tok(["what causes vitamin d deficiency"], return_tensors="np", padding=True)
sparse = model.encode(mx.array(enc["input_ids"]), mx.array(enc["attention_mask"]))  # (1, 30522)

Do not pass dtype="float32" for this pre-converted repository: its declared stored dtype is bfloat16. Load the upstream prithivida/Splade_PP_en_v1 checkpoint to create an fp32 conversion.

License

Apache-2.0, same as the upstream checkpoint.

Downloads last month
27
MLX
Hardware compatibility
Log In to add your hardware

Quantized

Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐Ÿ™‹ Ask for provider support

Model tree for NomaDamas/Splade_PP_en_v1-mlx

Finetuned
(1)
this model