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: 733 Bytes
580ed2b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | [project]
name = "laya-browser"
version = "0.1.0"
description = "laya fine-tuned as a browser-agent decision head: server, task suite, fine-tune pipeline"
requires-python = ">=3.11,<3.13"
dependencies = [
"laya>=0.3.4",
"torch>=2.6",
"transformers>=4.48",
"huggingface_hub>=0.25",
"httpx[http2]>=0.28",
"numpy>=1.24",
]
[project.optional-dependencies]
fast = ["tilelang>=0.1.14"] # TileLang fast path (code/kernels)
data = ["beautifulsoup4", "lxml", "datasets", "modelscope"] # Mind2Web conversion / dataset eval
browser = ["browser-harness==0.1.13"] # only for the live suite / crawling (jev-ultrafast side)
[tool.uv]
index-url = "https://pypi.tuna.tsinghua.edu.cn/simple"
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