Feature Extraction
Transformers
Safetensors
code
bert
syzkaller
syz-program
linux-kernel
code-encoder
masked-language-modeling
text-embeddings-inference
Instructions to use zzra1n/SyzEncoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zzra1n/SyzEncoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="zzra1n/SyzEncoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("zzra1n/SyzEncoder") model = AutoModel.from_pretrained("zzra1n/SyzEncoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from zzra1n/SyzEncoder: direct link, hf CLI and curl.
- Browser
- Download file 1.84 MB
-
https://huggingface.co/zzra1n/SyzEncoder/resolve/main/tokenizer.json
- Command line
-
hf download hf://zzra1n/SyzEncoder/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/zzra1n/SyzEncoder/resolve/main/tokenizer.json
1.84 MB
File too large to display, you can check the raw version instead.