Automatic Speech Recognition
Transformers
Safetensors
qwen3_asr
text-generation
speech
asr
indian-languages
indic
multilingual
heep
Instructions to use bc7ec356/heep-indic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bc7ec356/heep-indic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="bc7ec356/heep-indic")# Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("bc7ec356/heep-indic", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -167,11 +167,7 @@ Output: Curated dataset D*
|
|
| 167 |
- Significant reduction in computational resources and training time
|
| 168 |
|
| 169 |
|
| 170 |
-
##
|
| 171 |
-
|
| 172 |
-
**Addressing Q1 (Gain Attribution), Q2 (Baselines), and Q3 (Base Model Dependency)**
|
| 173 |
-
|
| 174 |
-
We apologize for the supplementary post after the rebuttal period. These results were finalized shortly after the deadline, and we wanted to ensure complete experimental evidence was available rather than leave placeholders.
|
| 175 |
|
| 176 |
|
| 177 |
#### Resources
|
|
@@ -226,8 +222,6 @@ Comparison of publicly-available models on the Hindi subset of the benchmark:
|
|
| 226 |
|
| 227 |
4. **Reproducibility.** Model weights, curation code, and training scripts for both backbones are at the anonymous repository.
|
| 228 |
|
| 229 |
-
*We hope Reviewers 2ezj, oXjG, and S4Jd also find this supplementary evidence relevant to their earlier questions on generalization and controlled multilingual evaluation.*
|
| 230 |
-
|
| 231 |
|
| 232 |
## Model Details
|
| 233 |
|
|
|
|
| 167 |
- Significant reduction in computational resources and training time
|
| 168 |
|
| 169 |
|
| 170 |
+
## Cross-Architecture Validation with HEEP-Indic
|
|
|
|
|
|
|
|
|
|
|
|
|
| 171 |
|
| 172 |
|
| 173 |
#### Resources
|
|
|
|
| 222 |
|
| 223 |
4. **Reproducibility.** Model weights, curation code, and training scripts for both backbones are at the anonymous repository.
|
| 224 |
|
|
|
|
|
|
|
| 225 |
|
| 226 |
## Model Details
|
| 227 |
|