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: 2,470 Bytes
adf912b 454b3e6 adf912b | 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 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 | """Shared helpers: model loading + pretty printing."""
import os, sys, time
os.environ.setdefault("USE_TF", "0")
os.environ.setdefault("TOKENIZERS_PARALLELISM", "false")
_AGENTS = {}
def get_agent(variant="english"):
"""variant: english | multilingual | typed"""
if variant in _AGENTS:
return _AGENTS[variant]
import laya
t = time.time()
if os.path.isdir(variant):
a = laya.load(variant)
elif variant == "english":
# download only the root checkpoint (the other subfolders are several GB each)
from huggingface_hub import snapshot_download
path = snapshot_download("convaiinnovations/laya", ignore_patterns=["multilingual/*", "typed-decisions/*"])
a = laya.load(path)
elif variant == "multilingual":
a = laya.load("convaiinnovations/laya", subfolder="multilingual")
else:
from huggingface_hub import snapshot_download
path = snapshot_download("convaiinnovations/laya", allow_patterns=["typed-decisions/*"])
a = laya.load(path, subfolder="typed-decisions")
print(f"[laya] loaded {variant} in {time.time()-t:.1f}s", file=sys.stderr)
if os.environ.get("LAYA_FAST", "1") == "1":
try:
sys.path.insert(0, os.path.join(os.path.dirname(os.path.abspath(__file__)), "..", "kernels"))
from fast_laya import accelerate
accelerate(a)
print("[laya] TileLang fast path enabled (LAYA_FAST=0 to disable)", file=sys.stderr)
except Exception as e:
print(f"[laya] fast path unavailable: {e}", file=sys.stderr)
_AGENTS[variant] = a
return a
def bar(p, width=20):
n = int(round(p * width))
return "█" * n + "░" * (width - n)
def show(result, indent=" "):
"""Pretty-print a laya predict() result."""
for name, a in result["answers"].items():
t = a["type"]
if t == "choice":
print(f"{indent}{name}: {a['choice']} (conf {a['confidence']:.2f})")
for k, v in sorted(a["probabilities"].items(), key=lambda kv: -kv[1]):
print(f"{indent} {bar(v)} {v:5.2f} {k}")
elif t == "score":
print(f"{indent}{name}: score={a['score']:.2f} (conf {a['confidence']:.2f})")
for k, v in a["probabilities"].items():
print(f"{indent} {bar(v)} {v:5.2f} {a['legend'][k]}")
else:
p = a["noul"]
print(f"{indent}{name}: P(true)={p:.2f} {bar(p)}")
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