Instructions to use anton-l/xtreme_s_xlsr_bart_covost with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anton-l/xtreme_s_xlsr_bart_covost with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="anton-l/xtreme_s_xlsr_bart_covost")# Load model directly from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq tokenizer = AutoTokenizer.from_pretrained("anton-l/xtreme_s_xlsr_bart_covost") model = AutoModelForSpeechSeq2Seq.from_pretrained("anton-l/xtreme_s_xlsr_bart_covost", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 4500
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 3172253677
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e148a27f673a9d4bd7609e676ab76484a670e28bbfd694454f7bb7ac56ce09bb
|
| 3 |
size 3172253677
|
runs/Mar15_11-47-16_hf-paris-dgx-station-1/events.out.tfevents.1647341269.hf-paris-dgx-station-1.3531342.0
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 sha256:388c3d3ec4133c2b1847329ba62f0d65b3880b4a4a000f9d471671f6e0e1790d
|
| 3 |
+
size 718748
|