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 tokenizer.json from Jibbalit/phi-4-multimodal-instruct-abliterated: direct link, hf CLI and curl.
- Browser
- Download file 15.5 MB
-
https://huggingface.co/Jibbalit/phi-4-multimodal-instruct-abliterated/resolve/main/tokenizer.json
- Command line
-
hf download hf://Jibbalit/phi-4-multimodal-instruct-abliterated/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Jibbalit/phi-4-multimodal-instruct-abliterated/resolve/main/tokenizer.json
15.5 MB
- Xet hash:
- ace3049a8e9776901c2b3cae286b82c3a124c5750c1ec8c2b94c404eb1e600bb
- Size of remote file:
- 15.5 MB
- SHA256:
- 4c1b9f641d4f8b7247b8d5007dd3b6a9f6a87cb5123134fe0d326f14d10c0585
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.