Model Details
Full Model IDmicrosoft/LLM2CLIP-Llama-3-8B-Instruct-CC-Finetuned
Pipeline / Taskzero-shot-classification
Library—
Downloads (all-time)31.2K
Likes47
Last Modified11/19/2024
Author / Orgmicrosoft
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("zero-shot-classification", model="microsoft/LLM2CLIP-Llama-3-8B-Instruct-CC-Finetuned")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
safetensorsllamaCLIPLLM2CLIPzero-shot-classificationcustom_codearxiv:2411.04997license:apache-2.0region:us
More zero-shot-classification Models
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Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🤖 Task: zero-shot-classification
This model is designed for the zero-shot-classification task. Explore more models for this use case.
All zero-shot-classification Models →📊 Popularity
⬇ Downloads31.2K
❤️ Community Likes47
🛠️ Requirements
- →Check docs for installation steps.
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.