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/run_phase2.sh from cklxx/laya-browser: direct link, hf CLI and curl.
- Browser
- Download file 3.75 kB
-
https://huggingface.co/cklxx/laya-browser/resolve/main/code/finetune/run_phase2.sh
- Command line
-
hf download hf://cklxx/laya-browser/code/finetune/run_phase2.sh
-
curl -L -o run_phase2.sh https://huggingface.co/cklxx/laya-browser/resolve/main/code/finetune/run_phase2.sh
3.75 kB
| # Phase 2: v18s (mmBERT-base, continue v17s, 1 epoch) and v18L (ModernBERT-large from typed-decisions, 2 epochs), same data: | |
| # everything v17s saw + webgym new kinds (gym/clean3_*) + webgym DAgger (dagger/d_*). Then suites A, B, C and webgym held-out. | |
| # Resumable: train.py resumes from <ckpt>/resume.pt; SKIP_BUILD=1 reuses the item files; STAGE=L|eval skips earlier stages. | |
| cd /home/ckl/projects/S/laya && source env.sh | |
| export PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True CKPT=1 COMPILE=0 LAYA_FMT=v3 LAYA_HEAD=768 MAX_TARGETS=40 FINAL_P=0.2 | |
| P=.venv/bin/python; O=finetune/out; I="bash finetune/infra.sh"; export INFRA_DIR=${INFRA_DIR:-/tmp/laya-infra} | |
| SNAP=$(ls -d ~/.cache/huggingface/hub/models--convaiinnovations--laya/snapshots/*/typed-decisions | head -1) | |
| bash finetune/infra.sh stop_s1; sleep 3 # chromium is shared with the other sessions: leave it running | |
| cat $O/rollout2_cases.*.jsonl > $O/rollout2_cases.jsonl | |
| cat $O/gym/*.jsonl > $O/gym_cases.jsonl | |
| cat $O/dagger/d_*.jsonl > $O/dagger_gym_cases.jsonl 2>/dev/null || : > $O/dagger_gym_cases.jsonl | |
| echo "== data: gym $(wc -l < $O/gym_cases.jsonl) webgym-dagger $(wc -l < $O/dagger_gym_cases.jsonl) m2w_sub $(wc -l < $O/m2w_sub_cases.jsonl)" | |
| SRC="$O/done_cases.jsonl $O/step2_cases.jsonl $O/m2w_cases.jsonl $O/rollout_cases.jsonl $O/rollout2_cases.jsonl $O/nnetnav_cases.jsonl $O/gym_cases.jsonl $O/m2w_sub_cases.jsonl $O/dagger_gym_cases.jsonl" | |
| train() { # $1 ckpt name, $2 base dir, $3 items dir, $4 epochs | |
| mkdir -p $3 | |
| if [ -z "$SKIP_BUILD" ] || [ ! -f $3/train_items.pt ]; then | |
| echo "== build $1"; LAYA_BASE=$2 $P finetune/build_items.py $O/pages.jsonl $O/cases.jsonl $3/ $SRC 2>&1 | grep -v Warn | tail -3 | |
| fi | |
| echo "== train $1 ($4 epochs from $(basename $2))"; LAYA_BASE=$2 $P finetune/train.py $3/train_items.pt $O/$1 $4 2>&1 | grep --line-buffered -E "=== epoch|saved|Error|Traceback|resumed" | |
| [ -f $O/$1/model.safetensors ] || { echo "training of $1 interrupted; rerun (SKIP_BUILD=1) to resume"; exit 0; } | |
| echo "== calibrate + eval $1"; $P finetune/calibrate.py $O/pages.jsonl $3/eval_cases.jsonl $PWD/$O/$1 2>&1 | grep -vE "TileLang|Warn|warn|Fetch" | tail -1 | |
| $P finetune/eval.py $O/pages.jsonl $3/eval_cases.jsonl $PWD/$O/$1 2>&1 | grep -E "operation acc| live | mind2web | webgym" | |
| } | |
| [ "$STAGE" = "L" ] || [ "$STAGE" = "eval" ] || train laya-browser-v18s $PWD/$O/laya-browser-v17s $O/items_s 1 | |
| [ "$STAGE" = "eval" ] || train laya-browser-v18L $SNAP $O/items_L 2 | |
| $I start_chrome >/dev/null; SGL_MEM=0.5 $I start_sglang Qwen/Qwen3-8B-AWQ >/dev/null; bash finetune/webgym/serve.sh restart >/dev/null | |
| until curl -s -m 3 http://127.0.0.1:30000/health >/dev/null; do sleep 5; done | |
| KINDS=$($P -c "import sys; sys.path.insert(0,'finetune/webgym'); import spec; print(','.join(spec.KINDS))") | |
| for CK in laya-browser-v18s laya-browser-v18L; do | |
| $I start_s1 $PWD/$O/$CK 60 >/dev/null | |
| echo "== $CK suite A x3"; (cd ../jev-ultrafast && REPEATS=3 SUITE_OUT=$PWD/../laya/$O/suiteA_$CK.json timeout 3600 .venv/bin/python ../laya/apps/browser_suite.py 2>&1 | grep -E "^==|per task") | |
| echo "== $CK suite B x3"; (cd ../jev-ultrafast && REPEATS=3 SUITE_OUT=$PWD/../laya/$O/suiteB_$CK.json timeout 3600 .venv/bin/python ../laya/apps/browser_suite_b.py 2>&1 | grep -E "^==|per task") | |
| [ -f apps/browser_suite_c.py ] && { echo "== $CK suite C x2"; (cd ../jev-ultrafast && REPEATS=2 SUITE_OUT=$PWD/../laya/$O/suiteC_$CK.json timeout 5400 .venv/bin/python ../laya/apps/browser_suite_c.py 2>&1 | grep -E "^==|per task|held-out"); } | |
| echo "== $CK webgym held-out ($KINDS)"; (cd ../jev-ultrafast && GYM_OUT=$PWD/../laya/$O/gym_eval_$CK.json timeout 5400 .venv/bin/python ../laya/finetune/webgym/eval_gym.py 10 $KINDS 60 2>&1 | grep -E "^==") | |
| done | |
| echo PHASE2_DONE | |