Feature Extraction
Transformers
Safetensors
Laya
English
multilingual
laya_browser
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)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("cklxx/laya-browser", trust_remote_code=True, device_map="auto") - Laya
How to use cklxx/laya-browser with Laya:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
File size: 3,630 Bytes
454b3e6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | 0/22123 {'ok': 31, 'skip': 0, 'err': 0, 'dom': 31, 'gold_text': 0, 'gold_dom': 27, 'no_gold': 4, 'mb': 69.319224} 13.8 MB/s
1000/22123 {'ok': 950, 'skip': 0, 'err': 54, 'dom': 943, 'gold_text': 9, 'gold_dom': 783, 'no_gold': 151, 'mb': 2127.8091719999993} 17.2 MB/s
2000/22123 {'ok': 1886, 'skip': 0, 'err': 117, 'dom': 1876, 'gold_text': 15, 'gold_dom': 1532, 'no_gold': 329, 'mb': 4302.848061999988} 17.8 MB/s
3000/22123 {'ok': 2784, 'skip': 0, 'err': 218, 'dom': 2769, 'gold_text': 29, 'gold_dom': 2393, 'no_gold': 347, 'mb': 6493.843384999993} 17.8 MB/s
4000/22123 {'ok': 3710, 'skip': 0, 'err': 291, 'dom': 3687, 'gold_text': 35, 'gold_dom': 3240, 'no_gold': 412, 'mb': 8329.139589} 17.2 MB/s
5000/22123 {'ok': 4658, 'skip': 0, 'err': 347, 'dom': 4634, 'gold_text': 45, 'gold_dom': 4101, 'no_gold': 487, 'mb': 10444.615218999994} 16.3 MB/s
6000/22123 {'ok': 5621, 'skip': 0, 'err': 382, 'dom': 5578, 'gold_text': 63, 'gold_dom': 4918, 'no_gold': 597, 'mb': 12609.828113999984} 16.3 MB/s
7000/22123 {'ok': 6598, 'skip': 0, 'err': 404, 'dom': 6555, 'gold_text': 68, 'gold_dom': 5816, 'no_gold': 668, 'mb': 14649.179696000041} 16.3 MB/s
8000/22123 {'ok': 7537, 'skip': 0, 'err': 466, 'dom': 7488, 'gold_text': 80, 'gold_dom': 6654, 'no_gold': 753, 'mb': 17744.917447000054} 17.3 MB/s
9000/22123 {'ok': 8487, 'skip': 0, 'err': 520, 'dom': 8437, 'gold_text': 93, 'gold_dom': 7501, 'no_gold': 841, 'mb': 19764.16036200014} 17.3 MB/s
10000/22123 {'ok': 9422, 'skip': 0, 'err': 592, 'dom': 9365, 'gold_text': 108, 'gold_dom': 8380, 'no_gold': 877, 'mb': 21959.78241200013} 17.3 MB/s
11000/22123 {'ok': 10281, 'skip': 0, 'err': 728, 'dom': 10225, 'gold_text': 115, 'gold_dom': 9181, 'no_gold': 928, 'mb': 23767.783094000075} 17.2 MB/s
12000/22123 {'ok': 11246, 'skip': 0, 'err': 764, 'dom': 11184, 'gold_text': 131, 'gold_dom': 10080, 'no_gold': 974, 'mb': 25850.519002000095} 17.1 MB/s
13000/22123 {'ok': 12122, 'skip': 0, 'err': 879, 'dom': 12059, 'gold_text': 145, 'gold_dom': 10844, 'no_gold': 1071, 'mb': 27349.249163000088} 16.9 MB/s
14000/22123 {'ok': 13029, 'skip': 0, 'err': 973, 'dom': 12964, 'gold_text': 160, 'gold_dom': 11669, 'no_gold': 1136, 'mb': 29427.23706500011} 16.9 MB/s
15000/22123 {'ok': 13948, 'skip': 0, 'err': 1062, 'dom': 13877, 'gold_text': 170, 'gold_dom': 12492, 'no_gold': 1217, 'mb': 32332.190318000186} 17.2 MB/s
16000/22123 {'ok': 14906, 'skip': 0, 'err': 1098, 'dom': 14834, 'gold_text': 184, 'gold_dom': 13318, 'no_gold': 1333, 'mb': 34411.627349000126} 17.2 MB/s
17000/22123 {'ok': 15782, 'skip': 0, 'err': 1228, 'dom': 15693, 'gold_text': 194, 'gold_dom': 14151, 'no_gold': 1349, 'mb': 37011.482945999975} 17.4 MB/s
18000/22123 {'ok': 16748, 'skip': 0, 'err': 1258, 'dom': 16617, 'gold_text': 227, 'gold_dom': 14972, 'no_gold': 1454, 'mb': 38897.240475999824} 17.3 MB/s
19000/22123 {'ok': 17710, 'skip': 0, 'err': 1291, 'dom': 17579, 'gold_text': 231, 'gold_dom': 15884, 'no_gold': 1500, 'mb': 40655.070045999855} 17.2 MB/s
20000/22123 {'ok': 18638, 'skip': 0, 'err': 1366, 'dom': 18490, 'gold_text': 233, 'gold_dom': 16777, 'no_gold': 1516, 'mb': 43213.31280099959} 17.4 MB/s
21000/22123 {'ok': 19561, 'skip': 0, 'err': 1442, 'dom': 19408, 'gold_text': 249, 'gold_dom': 17673, 'no_gold': 1522, 'mb': 45562.94377699968} 17.4 MB/s
22000/22123 {'ok': 20449, 'skip': 0, 'err': 1555, 'dom': 20287, 'gold_text': 270, 'gold_dom': 18498, 'no_gold': 1554, 'mb': 47437.25134199973} 17.3 MB/s
fetch done 3000 traces, 22123 steps {'ok': 20558, 'skip': 0, 'err': 1565, 'dom': 20391, 'gold_text': 273, 'gold_dom': 18600, 'no_gold': 1554, 'mb': 47784.77658299978}
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