Text Generation
PEFT
Safetensors
cybersecurity
defensive-security
malware-analysis
incident-response
red-team
blue-team
purple-team
conversational
Instructions to use KaztoRay/WhiteSpacer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use KaztoRay/WhiteSpacer with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("inclusionAI/Ling-3.0-tiny") model = PeftModel.from_pretrained(base_model, "KaztoRay/WhiteSpacer") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from KaztoRay/WhiteSpacer: direct link, hf CLI and curl.
- Browser
- Download file 12.2 MB
-
https://huggingface.co/KaztoRay/WhiteSpacer/resolve/main/tokenizer.json
- Command line
-
hf download hf://KaztoRay/WhiteSpacer/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/KaztoRay/WhiteSpacer/resolve/main/tokenizer.json
12.2 MB
- Xet hash:
- a99e00d9a1ae89368bc0573957df109a67e26a1e30a05c44835f92d36661896d
- Size of remote file:
- 12.2 MB
- SHA256:
- 40fb9d7d7795b8bd305aeff39ce9963f3f450915b9553f2938e009be9a1fed60
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