Instructions to use ibrainf/result with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ibrainf/result with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="ibrainf/result")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("ibrainf/result") model = AutoModelForTextToSpectrogram.from_pretrained("ibrainf/result", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 500
Browse files
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 577789320
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:56060d80f7a9265eb3c89ccc042d25a37b4e822a898bc469e71aa742d98113e2
|
| 3 |
size 577789320
|
runs/Dec28_16-33-13_227775606f54/events.out.tfevents.1735403758.227775606f54.383.0
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:c65c4a5f4e4f7efb563eea2b744d843c28c684b7a448efef5f3401df587f07d8
|
| 3 |
+
size 12258
|