Text Generation
PEFT
Safetensors
English
granite
lora
meetings
action-items
decisions
information-extraction
local-inference
conversational
Instructions to use Privoid-ai/Privoid-Action-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Privoid-ai/Privoid-Action-1B with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("ibm-granite/granite-4.0-1b") model = PeftModel.from_pretrained(base_model, "Privoid-ai/Privoid-Action-1B") - Notebooks
- Google Colab
- Kaggle
Privoid Action-1B experimental preview (LoRA adapter, validator, API, locked test results)
b68d688 verified Download tokenizer.json from Privoid-ai/Privoid-Action-1B: direct link, hf CLI and curl.
- Browser
- Download file 7.15 MB
-
https://huggingface.co/Privoid-ai/Privoid-Action-1B/resolve/main/tokenizer.json
- Command line
-
hf download hf://Privoid-ai/Privoid-Action-1B/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Privoid-ai/Privoid-Action-1B/resolve/main/tokenizer.json
7.15 MB
File too large to display, you can check the raw version instead.