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
abliterated
uncensored
custom_code
Instructions to use Jibbalit/phi-4-multimodal-instruct-abliterated with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jibbalit/phi-4-multimodal-instruct-abliterated with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Jibbalit/phi-4-multimodal-instruct-abliterated", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Jibbalit/phi-4-multimodal-instruct-abliterated", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from Jibbalit/phi-4-multimodal-instruct-abliterated: direct link, hf CLI and curl.
- Browser
- Download file 496 Bytes
-
https://huggingface.co/Jibbalit/phi-4-multimodal-instruct-abliterated/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://Jibbalit/phi-4-multimodal-instruct-abliterated/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/Jibbalit/phi-4-multimodal-instruct-abliterated/resolve/main/preprocessor_config.json
496 Bytes
| { | |
| "auto_map": { | |
| "AutoProcessor": "processing_phi4mm.Phi4MMProcessor", | |
| "AutoImageProcessor": "processing_phi4mm.Phi4MMImageProcessor", | |
| "AutoFeatureExtractor": "processing_phi4mm.Phi4MMAudioFeatureExtractor" | |
| }, | |
| "image_processor_type": "Phi4MMImageProcessor", | |
| "processor_class": "Phi4MMProcessor", | |
| "feature_extractor_type": "Phi4MMAudioFeatureExtractor", | |
| "audio_compression_rate": 8, | |
| "audio_downsample_rate": 1, | |
| "audio_feat_stride": 1, | |
| "dynamic_hd": 36 | |
| } | |