Instructions to use Scezui/LLMv3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Scezui/LLMv3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Scezui/LLMv3")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("Scezui/LLMv3") model = AutoModelForTokenClassification.from_pretrained("Scezui/LLMv3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
|
Download README.md from Scezui/LLMv3: direct link, hf CLI and curl.
- Browser
- Download file 25 Bytes
-
https://huggingface.co/Scezui/LLMv3/resolve/main/README.md
- Command line
-
hf download hf://Scezui/LLMv3/README.md
-
curl -L -o README.md https://huggingface.co/Scezui/LLMv3/resolve/main/README.md
25 Bytes
metadata
license: unknown