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
Download code/finetune/infra.sh from cklxx/laya-browser: direct link, hf CLI and curl.
- Browser
- Download file 2.45 kB
-
https://huggingface.co/cklxx/laya-browser/resolve/main/code/finetune/infra.sh
- Command line
-
hf download hf://cklxx/laya-browser/code/finetune/infra.sh
-
curl -L -o infra.sh https://huggingface.co/cklxx/laya-browser/resolve/main/code/finetune/infra.sh
2.45 kB
| # infra.sh start_chrome | start_sglang [model] | start_llama [gguf] | start_s1 <ckpt_dir> [maxopt] | stop_s1 | stop_all | status | |
| S=${INFRA_DIR:-/tmp/laya-infra}; mkdir -p $S | |
| L=~/projects/S/laya | |
| case "$1" in | |
| start_chrome) | |
| curl -s -m 3 http://127.0.0.1:9222/json/version >/dev/null && { echo chrome up; exit 0; } | |
| nohup chromium --headless=new ${CHROME_EXTRA:-} --remote-debugging-port=9222 --user-data-dir=$S/chrome-profile --window-size=1120,780 --no-first-run --lang=en-US --accept-lang=en-US,en about:blank >$S/chrome.log 2>&1 & | |
| sleep 3; curl -s -m 3 http://127.0.0.1:9222/json/version | head -c 120; echo ;; | |
| start_sglang) | |
| M=${2:-Qwen/Qwen3-8B-AWQ} | |
| curl -s -m 3 http://127.0.0.1:30000/health >/dev/null && { echo sglang up; exit 0; } | |
| cd $L; HF_HUB_OFFLINE=1 nohup ~/sglang-venv/bin/python -m sglang.launch_server --model-path $M --port 30000 --mem-fraction-static ${SGL_MEM:-0.35} --context-length 8192 --reasoning-parser qwen3 >$S/sglang.log 2>&1 & | |
| echo "sglang starting (pid $!)";; | |
| start_llama) # local Qwen3.6-35B-A3B (GGUF, MoE experts partly on CPU) on :30000, OpenAI-compatible; replaces sglang | |
| curl -s -m 3 --noproxy '*' http://127.0.0.1:30000/health >/dev/null && { echo "llm up"; exit 0; } | |
| M=${2:-$HOME/models/qwen3.6-35b-a3b/Qwen3.6-35B-A3B-UD-IQ4_XS.gguf} | |
| nohup ~/.local/share/llama.cpp/build/bin/llama-server -m $M --port 30000 --host 127.0.0.1 -ngl 99 --n-cpu-moe ${LLAMA_CPU_MOE:-26} \ | |
| -c ${LLAMA_CTX:-24576} -np ${LLAMA_PAR:-3} --jinja -fa on --no-webui >$S/llama.log 2>&1 & | |
| echo "llama-server starting (pid $!)";; | |
| start_s1) | |
| bash $0 stop_s1 | |
| cd $L; source env.sh; nohup env ESCALATE_TAU=${ESCALATE_TAU:-0} .venv/bin/python apps/systemone_server.py 8791 "$2" ${3:-999} >$S/s1.log 2>&1 & | |
| for i in $(seq 1 90); do curl -s -m 2 http://127.0.0.1:8791/ >/dev/null 2>&1 && { echo "s1 up ($2)"; exit 0; }; sleep 2; done; echo "s1 FAILED"; tail -5 $S/s1.log;; | |
| stop_chrome) pkill -f 'remote-debugging-port=922[2]' 2>/dev/null; sleep 2;; | |
| stop_s1) pkill -f 'apps/systemone_serve[r]' 2>/dev/null; sleep 1;; | |
| stop_all) bash $0 stop_s1; pkill -f 'sglang.launch_serve[r]' 2>/dev/null; pkill -f 'bin/llama-serve[r]' 2>/dev/null; pkill -f 'remote-debugging-port=9222' 2>/dev/null; echo stopped;; | |
| status) for p in 9222 8791 30000; do (ss -ltn | grep -q ":$p ") && echo "$p up" || echo "$p down"; done; nvidia-smi --query-gpu=memory.used --format=csv,noheader;; | |
| esac | |