Automatic Speech Recognition
Transformers
Safetensors
phi4mm
text-generation
nlp
code
audio
speech-summarization
speech-translation
visual-question-answering
phi-4-multimodal
phi
phi-4-mini
custom_code
Instructions to use IronWolfAI/GoldenCrow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IronWolfAI/GoldenCrow with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="IronWolfAI/GoldenCrow", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("IronWolfAI/GoldenCrow", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 734f733651b1be9cde9c0f12edf53d03c41bd7b13a30fbd0af4f43be5bcf0b0e
- Size of remote file:
- 738 MB
- SHA256:
- 1620b16722edf701038bf66e3cd46412c7cc5458e58df89e9f92cedb71fcbde8
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