Instructions to use hr16/multilingual_spin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hr16/multilingual_spin with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hr16/multilingual_spin")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hr16/multilingual_spin") model = AutoModel.from_pretrained("hr16/multilingual_spin", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 17,091 Bytes
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library_name: transformers
datasets:
- mythicinfinity/libritts
- ylacombe/cml-tts
base_model:
- facebook/hubert-base-ls960
---
Multilingual speaker-invariant speech content encoder based on [SPIN method](https://arxiv.org/abs/2305.11072) taken from [FreeSVC](https://huggingface.co/alefiury/free-svc), converted to transformers library format.
Usage:
```py
from transformers import AutoProcessor, HubertModel
feature_extractor = AutoFeatureExtractor.from_pretrained("hr16/multilingual_spin")
model = HubertModel.from_pretrained("hr16/multilingual_spin")
audio_input = torch.randn(16000) # 1 second of audio at 16kHz
inputs = feature_extractor(audio_input, sampling_rate=16000, return_tensors="pt")
with torch.no_grad():
outputs = model(**inputs)
print(outputs.last_hidden_state.shape)
```
Conversion code:
```py
import re
import torch
def convert_hubert_s3prl_to_transformers(model, checkpoint_path: str):
# 1. Load checkpoint
state_dict = torch.load(checkpoint_path, map_location="cpu", weights_only=False)
if "model" in state_dict:
state_dict = state_dict["model"]
elif "state_dict" in state_dict:
state_dict = state_dict["state_dict"]
hf_state_dict = {}
# 2. Map weights
for key, value in state_dict.items():
# Skip unused pretraining components
if (
key.startswith("pred_head")
or key.startswith("loss_module")
or "label_embs_concat" in key
):
continue
# Mask embedding
if key == "encoder.model.mask_emb":
hf_state_dict["masked_spec_embed"] = value
continue
# Feature extractor group norm / conv layers
if "feature_extractor.conv_layers" in key:
# e.g.: encoder.model.feature_extractor.conv_layers.0.0.weight -> feature_extractor.conv_layers.0.conv.weight
# e.g.: encoder.model.feature_extractor.conv_layers.0.2.weight -> feature_extractor.conv_layers.0.layer_norm.weight
match = re.search(r"conv_layers\.(\d+)\.(\d+)\.(weight|bias)", key)
if match:
layer_idx, sub_idx, param_name = match.groups()
if sub_idx == "0":
hf_key = f"feature_extractor.conv_layers.{layer_idx}.conv.{param_name}"
elif sub_idx == "2":
hf_key = f"feature_extractor.conv_layers.{layer_idx}.layer_norm.{param_name}"
hf_state_dict[hf_key] = value
continue
# Feature projection layer norm
if key in ("encoder.model.layer_norm.weight", "encoder.model.layer_norm.bias"):
param_name = key.split(".")[-1]
hf_state_dict[f"feature_projection.layer_norm.{param_name}"] = value
continue
# Feature projection linear layer
if "post_extract_proj" in key:
param_name = key.split(".")[-1]
hf_state_dict[f"feature_projection.projection.{param_name}"] = value
continue
# Positional Convolution Embedding
if "pos_conv.0" in key:
param_name = key.split(".")[-1]
# Handles weight_v, weight_g, bias
hf_state_dict[f"encoder.pos_conv_embed.conv.{param_name}"] = value
continue
# Encoder pre-LayerNorm
if key in (
"encoder.model.encoder.layer_norm.weight",
"encoder.model.encoder.layer_norm.bias",
):
param_name = key.split(".")[-1]
hf_state_dict[f"encoder.layer_norm.{param_name}"] = value
continue
# Encoder Transformer Layers
if "encoder.model.encoder.layers." in key:
# Map layer components
m = re.match(
r"encoder\.model\.encoder\.layers\.(\d+)\.(.+)", key
)
if m:
layer_idx, rest = m.groups()
prefix = f"encoder.layers.{layer_idx}"
if "self_attn." in rest:
# self_attn.{q,k,v,out}_proj.{weight,bias}
attn_component = rest.replace("self_attn.", "attention.")
hf_state_dict[f"{prefix}.{attn_component}"] = value
elif "self_attn_layer_norm." in rest:
param_name = rest.split(".")[-1]
hf_state_dict[f"{prefix}.layer_norm.{param_name}"] = value
elif "fc1." in rest:
param_name = rest.split(".")[-1]
hf_state_dict[
f"{prefix}.feed_forward.intermediate_dense.{param_name}"
] = value
elif "fc2." in rest:
param_name = rest.split(".")[-1]
hf_state_dict[
f"{prefix}.feed_forward.output_dense.{param_name}"
] = value
elif "final_layer_norm." in rest:
param_name = rest.split(".")[-1]
hf_state_dict[f"{prefix}.final_layer_norm.{param_name}"] = value
continue
print(f"Unmapped key: {key}")
model.load_state_dict(hf_state_dict)
return model
from transformers import HubertModel
orig_hubert = HubertModel.from_pretrained("facebook/hubert-base-ls960")
spin = convert_hubert_s3prl_to_transformers(HubertModel.from_pretrained("facebook/hubert-base-ls960"), "spin.ckpt")
spin.push_to_hub("hr16/multilingual_spin")
```
State dict mean-square differences:
```
masked_spec_embed diff: 0.0
feature_extractor.conv_layers.0.conv.weight diff: 0.0
feature_extractor.conv_layers.0.layer_norm.weight diff: 0.0
feature_extractor.conv_layers.0.layer_norm.bias diff: 0.0
feature_extractor.conv_layers.1.conv.weight diff: 0.0
feature_extractor.conv_layers.2.conv.weight diff: 0.0
feature_extractor.conv_layers.3.conv.weight diff: 0.0
feature_extractor.conv_layers.4.conv.weight diff: 0.0
feature_extractor.conv_layers.5.conv.weight diff: 0.0
feature_extractor.conv_layers.6.conv.weight diff: 0.0
feature_projection.layer_norm.weight diff: 0.0
feature_projection.layer_norm.bias diff: 0.0
feature_projection.projection.weight diff: 0.0
feature_projection.projection.bias diff: 0.0
encoder.pos_conv_embed.conv.bias diff: 0.0
encoder.pos_conv_embed.conv.parametrizations.weight.original0 diff: 0.0
encoder.pos_conv_embed.conv.parametrizations.weight.original1 diff: 0.0
encoder.layer_norm.weight diff: 0.0
encoder.layer_norm.bias diff: 0.0
encoder.layers.0.attention.k_proj.weight diff: 0.0
encoder.layers.0.attention.k_proj.bias diff: 0.0
encoder.layers.0.attention.v_proj.weight diff: 0.0
encoder.layers.0.attention.v_proj.bias diff: 0.0
encoder.layers.0.attention.q_proj.weight diff: 0.0
encoder.layers.0.attention.q_proj.bias diff: 0.0
encoder.layers.0.attention.out_proj.weight diff: 0.0
encoder.layers.0.attention.out_proj.bias diff: 0.0
encoder.layers.0.layer_norm.weight diff: 0.0
encoder.layers.0.layer_norm.bias diff: 0.0
encoder.layers.0.feed_forward.intermediate_dense.weight diff: 0.0
encoder.layers.0.feed_forward.intermediate_dense.bias diff: 0.0
encoder.layers.0.feed_forward.output_dense.weight diff: 0.0
encoder.layers.0.feed_forward.output_dense.bias diff: 0.0
encoder.layers.0.final_layer_norm.weight diff: 0.0
encoder.layers.0.final_layer_norm.bias diff: 0.0
encoder.layers.1.attention.k_proj.weight diff: 0.0
encoder.layers.1.attention.k_proj.bias diff: 0.0
encoder.layers.1.attention.v_proj.weight diff: 0.0
encoder.layers.1.attention.v_proj.bias diff: 0.0
encoder.layers.1.attention.q_proj.weight diff: 0.0
encoder.layers.1.attention.q_proj.bias diff: 0.0
encoder.layers.1.attention.out_proj.weight diff: 0.0
encoder.layers.1.attention.out_proj.bias diff: 0.0
encoder.layers.1.layer_norm.weight diff: 0.0
encoder.layers.1.layer_norm.bias diff: 0.0
encoder.layers.1.feed_forward.intermediate_dense.weight diff: 0.0
encoder.layers.1.feed_forward.intermediate_dense.bias diff: 0.0
encoder.layers.1.feed_forward.output_dense.weight diff: 0.0
encoder.layers.1.feed_forward.output_dense.bias diff: 0.0
encoder.layers.1.final_layer_norm.weight diff: 0.0
encoder.layers.1.final_layer_norm.bias diff: 0.0
encoder.layers.2.attention.k_proj.weight diff: 0.0
encoder.layers.2.attention.k_proj.bias diff: 0.0
encoder.layers.2.attention.v_proj.weight diff: 0.0
encoder.layers.2.attention.v_proj.bias diff: 0.0
encoder.layers.2.attention.q_proj.weight diff: 0.0
encoder.layers.2.attention.q_proj.bias diff: 0.0
encoder.layers.2.attention.out_proj.weight diff: 0.0
encoder.layers.2.attention.out_proj.bias diff: 0.0
encoder.layers.2.layer_norm.weight diff: 0.0
encoder.layers.2.layer_norm.bias diff: 0.0
encoder.layers.2.feed_forward.intermediate_dense.weight diff: 0.0
encoder.layers.2.feed_forward.intermediate_dense.bias diff: 0.0
encoder.layers.2.feed_forward.output_dense.weight diff: 0.0
encoder.layers.2.feed_forward.output_dense.bias diff: 0.0
encoder.layers.2.final_layer_norm.weight diff: 0.0
encoder.layers.2.final_layer_norm.bias diff: 0.0
encoder.layers.3.attention.k_proj.weight diff: 0.0
encoder.layers.3.attention.k_proj.bias diff: 0.0
encoder.layers.3.attention.v_proj.weight diff: 0.0
encoder.layers.3.attention.v_proj.bias diff: 0.0
encoder.layers.3.attention.q_proj.weight diff: 0.0
encoder.layers.3.attention.q_proj.bias diff: 0.0
encoder.layers.3.attention.out_proj.weight diff: 0.0
encoder.layers.3.attention.out_proj.bias diff: 0.0
encoder.layers.3.layer_norm.weight diff: 0.0
encoder.layers.3.layer_norm.bias diff: 0.0
encoder.layers.3.feed_forward.intermediate_dense.weight diff: 0.0
encoder.layers.3.feed_forward.intermediate_dense.bias diff: 0.0
encoder.layers.3.feed_forward.output_dense.weight diff: 0.0
encoder.layers.3.feed_forward.output_dense.bias diff: 0.0
encoder.layers.3.final_layer_norm.weight diff: 0.0
encoder.layers.3.final_layer_norm.bias diff: 0.0
encoder.layers.4.attention.k_proj.weight diff: 0.0
encoder.layers.4.attention.k_proj.bias diff: 0.0
encoder.layers.4.attention.v_proj.weight diff: 0.0
encoder.layers.4.attention.v_proj.bias diff: 0.0
encoder.layers.4.attention.q_proj.weight diff: 0.0
encoder.layers.4.attention.q_proj.bias diff: 0.0
encoder.layers.4.attention.out_proj.weight diff: 0.0
encoder.layers.4.attention.out_proj.bias diff: 0.0
encoder.layers.4.layer_norm.weight diff: 0.0
encoder.layers.4.layer_norm.bias diff: 0.0
encoder.layers.4.feed_forward.intermediate_dense.weight diff: 0.0
encoder.layers.4.feed_forward.intermediate_dense.bias diff: 0.0
encoder.layers.4.feed_forward.output_dense.weight diff: 0.0
encoder.layers.4.feed_forward.output_dense.bias diff: 0.0
encoder.layers.4.final_layer_norm.weight diff: 0.0
encoder.layers.4.final_layer_norm.bias diff: 0.0
encoder.layers.5.attention.k_proj.weight diff: 0.0
encoder.layers.5.attention.k_proj.bias diff: 0.0
encoder.layers.5.attention.v_proj.weight diff: 0.0
encoder.layers.5.attention.v_proj.bias diff: 0.0
encoder.layers.5.attention.q_proj.weight diff: 0.0
encoder.layers.5.attention.q_proj.bias diff: 0.0
encoder.layers.5.attention.out_proj.weight diff: 0.0
encoder.layers.5.attention.out_proj.bias diff: 0.0
encoder.layers.5.layer_norm.weight diff: 0.0
encoder.layers.5.layer_norm.bias diff: 0.0
encoder.layers.5.feed_forward.intermediate_dense.weight diff: 0.0
encoder.layers.5.feed_forward.intermediate_dense.bias diff: 0.0
encoder.layers.5.feed_forward.output_dense.weight diff: 0.0
encoder.layers.5.feed_forward.output_dense.bias diff: 0.0
encoder.layers.5.final_layer_norm.weight diff: 0.0
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encoder.layers.6.attention.v_proj.weight diff: 0.0
encoder.layers.6.attention.v_proj.bias diff: 0.0
encoder.layers.6.attention.q_proj.weight diff: 0.0
encoder.layers.6.attention.q_proj.bias diff: 0.0
encoder.layers.6.attention.out_proj.weight diff: 0.0
encoder.layers.6.attention.out_proj.bias diff: 0.0
encoder.layers.6.layer_norm.weight diff: 0.0
encoder.layers.6.layer_norm.bias diff: 0.0
encoder.layers.6.feed_forward.intermediate_dense.weight diff: 0.0
encoder.layers.6.feed_forward.intermediate_dense.bias diff: 0.0
encoder.layers.6.feed_forward.output_dense.weight diff: 0.0
encoder.layers.6.feed_forward.output_dense.bias diff: 0.0
encoder.layers.6.final_layer_norm.weight diff: 0.0
encoder.layers.6.final_layer_norm.bias diff: 0.0
encoder.layers.7.attention.k_proj.weight diff: 0.0
encoder.layers.7.attention.k_proj.bias diff: 0.0
encoder.layers.7.attention.v_proj.weight diff: 0.0
encoder.layers.7.attention.v_proj.bias diff: 0.0
encoder.layers.7.attention.q_proj.weight diff: 0.0
encoder.layers.7.attention.q_proj.bias diff: 0.0
encoder.layers.7.attention.out_proj.weight diff: 0.0
encoder.layers.7.attention.out_proj.bias diff: 0.0
encoder.layers.7.layer_norm.weight diff: 0.0
encoder.layers.7.layer_norm.bias diff: 0.0
encoder.layers.7.feed_forward.intermediate_dense.weight diff: 0.0
encoder.layers.7.feed_forward.intermediate_dense.bias diff: 0.0
encoder.layers.7.feed_forward.output_dense.weight diff: 0.0
encoder.layers.7.feed_forward.output_dense.bias diff: 0.0
encoder.layers.7.final_layer_norm.weight diff: 0.0
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encoder.layers.8.attention.k_proj.weight diff: 0.0
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encoder.layers.8.attention.v_proj.weight diff: 0.0
encoder.layers.8.attention.v_proj.bias diff: 0.0
encoder.layers.8.attention.q_proj.weight diff: 0.0
encoder.layers.8.attention.q_proj.bias diff: 0.0
encoder.layers.8.attention.out_proj.weight diff: 0.0
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encoder.layers.9.feed_forward.intermediate_dense.bias diff: 0.0
encoder.layers.9.feed_forward.output_dense.weight diff: 0.0
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encoder.layers.9.final_layer_norm.bias diff: 0.0
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encoder.layers.10.attention.v_proj.weight diff: 0.001084218267351389
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encoder.layers.10.attention.q_proj.weight diff: 0.002644478576257825
encoder.layers.10.attention.q_proj.bias diff: 0.0009331119363196194
encoder.layers.10.attention.out_proj.weight diff: 0.0009169431868940592
encoder.layers.10.attention.out_proj.bias diff: 0.00011753084982046857
encoder.layers.10.layer_norm.weight diff: 0.004704533610492945
encoder.layers.10.layer_norm.bias diff: 0.00040463244658894837
encoder.layers.10.feed_forward.intermediate_dense.weight diff: 0.002256407169625163
encoder.layers.10.feed_forward.intermediate_dense.bias diff: 8.606249321019277e-05
encoder.layers.10.feed_forward.output_dense.weight diff: 0.0017423474928364158
encoder.layers.10.feed_forward.output_dense.bias diff: 7.794254634063691e-05
encoder.layers.10.final_layer_norm.weight diff: 0.003364397445693612
encoder.layers.10.final_layer_norm.bias diff: 0.000663460697978735
encoder.layers.11.attention.k_proj.weight diff: 0.0019817741122096777
encoder.layers.11.attention.k_proj.bias diff: 0.032148730009794235
encoder.layers.11.attention.v_proj.weight diff: 0.0010857016313821077
encoder.layers.11.attention.v_proj.bias diff: 0.00020938993839081377
encoder.layers.11.attention.q_proj.weight diff: 0.002357392804697156
encoder.layers.11.attention.q_proj.bias diff: 0.0008044671267271042
encoder.layers.11.attention.out_proj.weight diff: 0.0011331378482282162
encoder.layers.11.attention.out_proj.bias diff: 0.00014901244139764458
encoder.layers.11.layer_norm.weight diff: 0.0027753293979912996
encoder.layers.11.layer_norm.bias diff: 0.0056587993167340755
encoder.layers.11.feed_forward.intermediate_dense.weight diff: 0.0032594590447843075
encoder.layers.11.feed_forward.intermediate_dense.bias diff: 0.0002475830551702529
encoder.layers.11.feed_forward.output_dense.weight diff: 0.002621536375954747
encoder.layers.11.feed_forward.output_dense.bias diff: 2.9405724490061402e-05
encoder.layers.11.final_layer_norm.weight diff: 0.002755063585937023
encoder.layers.11.final_layer_norm.bias diff: 0.00021274278697092086
``` |