Dedicated Endpoints

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README

License: other

Quick start (Python)

bash

pip install transformers peft torch

python

from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel
base = "Qwen/Qwen3.6-27B"
adapter = "canxp-ai/maplept-large-canada-legal-cpt-4d6666a7"
tokenizer = AutoTokenizer.from_pretrained(base, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
base, torch_dtype="bfloat16", device_map="auto", trust_remote_code=True
)
model = PeftModel.from_pretrained(model, adapter)
prompt = "Hello!"
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
out = model.generate(**inputs, max_new_tokens=200)
print(tokenizer.decode(out[0], skip_special_tokens=True))

CLI download

bash

pip install -U "huggingface_hub[cli]"
huggingface-cli download canxp-ai/maplept-large-canada-legal-cpt-4d6666a7 --local-dir ./maplept-large-canada-legal-cpt

Training details

  • Base model: Qwen/Qwen3.6-27B
  • Method: CPT
  • Epochs: 2
  • Context length: 8192
  • Validation split: 0.1

This adapter inherits the upstream license of the base model. See LICENSE_NOTICE.txt in this repo for details.

Model provider

canxp-ai

Model tree

Base

Qwen/Qwen3.6-27B

Adapter

this model

Modalities

Input

Video, Text, Image

Output

Text

Pricing

Dedicated Endpoints

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Supported Functionality

Model APIs

Dedicated Endpoints

Container

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