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
| { | |
| "auto_mapping": null, | |
| "base_model_name_or_path": "TBA", | |
| "bias": "none", | |
| "fan_in_fan_out": false, | |
| "inference_mode": true, | |
| "init_lora_weights": true, | |
| "layers_pattern": null, | |
| "layers_to_transform": null, | |
| "lora_alpha": 640, | |
| "lora_dropout": 0.01, | |
| "modules_to_save": [], | |
| "peft_type": "LORA", | |
| "r": 320, | |
| "revision": null, | |
| "target_modules": [ | |
| "qkv_proj", | |
| "o_proj", | |
| "gate_up_proj", | |
| "down_proj" | |
| ], | |
| "task_type": "CAUSAL_LM" | |
| } |