Instructions to use scribe-project/wav2vec2-large-voxrex-300m-radio with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scribe-project/wav2vec2-large-voxrex-300m-radio with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="scribe-project/wav2vec2-large-voxrex-300m-radio")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("scribe-project/wav2vec2-large-voxrex-300m-radio") model = AutoModelForCTC.from_pretrained("scribe-project/wav2vec2-large-voxrex-300m-radio", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
2a783c3
1
Parent(s): 7413c08
Training in progress, step 500
Browse files- config.json +1 -1
- pytorch_model.bin +2 -2
- training_args.bin +2 -2
config.json
CHANGED
|
@@ -109,7 +109,7 @@
|
|
| 109 |
1
|
| 110 |
],
|
| 111 |
"torch_dtype": "float32",
|
| 112 |
-
"transformers_version": "4.
|
| 113 |
"use_weighted_layer_sum": false,
|
| 114 |
"vocab_size": 37,
|
| 115 |
"xvector_output_dim": 512
|
|
|
|
| 109 |
1
|
| 110 |
],
|
| 111 |
"torch_dtype": "float32",
|
| 112 |
+
"transformers_version": "4.25.1",
|
| 113 |
"use_weighted_layer_sum": false,
|
| 114 |
"vocab_size": 37,
|
| 115 |
"xvector_output_dim": 512
|
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:6d1dbcda0b454da09ce25620fa58fd723ba342ef22eb99edd96b146c4a73fb42
|
| 3 |
+
size 1262053549
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:94ce7d891e4d2c55edb02fd0fb7bff38dcd5608a1cfa545c4e6cc48f13c403b8
|
| 3 |
+
size 3579
|