Instructions to use rajat99/Fine_Tuning_XLSR_300M_testing_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rajat99/Fine_Tuning_XLSR_300M_testing_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="rajat99/Fine_Tuning_XLSR_300M_testing_model")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("rajat99/Fine_Tuning_XLSR_300M_testing_model") model = AutoModelForCTC.from_pretrained("rajat99/Fine_Tuning_XLSR_300M_testing_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1262210673
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:3db831c2c86b9baf112dcad47a08f41d49611d4b4069c43020cfa9d5c854c6b6
|
| 3 |
size 1262210673
|
runs/Jul12_10-25-19_55e2a1fbb692/events.out.tfevents.1657622063.55e2a1fbb692.491.0
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 sha256:31f913bc7b638b2ed69e776ca7f71cea465b7667f210fb28c4b18617d3987112
|
| 3 |
+
size 5043
|