Feature Extraction
Transformers
Safetensors
English
multilingual
laya_browser
laya
custom_code
system-1
browser-agent
web-navigation
decision-model
mmbert
mind2web
tilelang
Instructions to use cklxx/laya-browser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cklxx/laya-browser with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="cklxx/laya-browser", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("cklxx/laya-browser", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 554 Bytes
adf912b 454b3e6 adf912b 454b3e6 adf912b | 1 2 3 4 5 6 7 8 9 | export HF_ENDPOINT=https://hf-mirror.com
export USE_TF=0
# hf-mirror redirects LFS files to *.xethub.hf.co, which is reachable direct: keep it off the metered proxy
case ",$no_proxy," in *xethub*) ;; *) export no_proxy="$no_proxy,.xethub.hf.co" NO_PROXY="$no_proxy,.xethub.hf.co";; esac
export UV_INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple
export PIP_INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple
# proxy stays on: shell no_proxy (2026-09-21) routes mirrors direct; huggingface.co and github.com need it
export PATH="$HOME/.local/bin:$PATH"
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