Instructions to use breadberry-prime/ylabs-data-heidi-medium-entrypoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use breadberry-prime/ylabs-data-heidi-medium-entrypoint with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="breadberry-prime/ylabs-data-heidi-medium-entrypoint")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("breadberry-prime/ylabs-data-heidi-medium-entrypoint") model = AutoModelForSpeechSeq2Seq.from_pretrained("breadberry-prime/ylabs-data-heidi-medium-entrypoint", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload WhisperForConditionalGeneration
Browse files- config.json +1 -1
- model.safetensors +2 -2
config.json
CHANGED
|
@@ -51,5 +51,5 @@
|
|
| 51 |
"transformers_version": "4.46.0.dev0",
|
| 52 |
"use_cache": true,
|
| 53 |
"use_weighted_layer_sum": false,
|
| 54 |
-
"vocab_size":
|
| 55 |
}
|
|
|
|
| 51 |
"transformers_version": "4.46.0.dev0",
|
| 52 |
"use_cache": true,
|
| 53 |
"use_weighted_layer_sum": false,
|
| 54 |
+
"vocab_size": 7122
|
| 55 |
}
|
model.safetensors
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:f7f29bf9a5ec5482c14d2bf9425d69f51c1ac3a2179aaa811d3c305f20cefddf
|
| 3 |
+
size 2901448640
|