Instructions to use Premchan369/Q-TensorFormer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Premchan369/Q-TensorFormer with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Premchan369/Q-TensorFormer", trust_remote_code=True)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("Premchan369/Q-TensorFormer", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Premchan369/Q-TensorFormer with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Premchan369/Q-TensorFormer"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Premchan369/Q-TensorFormer",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Premchan369/Q-TensorFormer

SGLang

How to use Premchan369/Q-TensorFormer with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Premchan369/Q-TensorFormer" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Premchan369/Q-TensorFormer",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Premchan369/Q-TensorFormer" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Premchan369/Q-TensorFormer",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Premchan369/Q-TensorFormer with Docker Model Runner:
```
docker model run hf.co/Premchan369/Q-TensorFormer
```

Q-TensorFormer / .github /workflows /ci.yml

Premchandyadav369

feat(10/10): add pyproject.toml packaging, multi-stage CI workflow, Colab badge, and trained tokenizer in app.py

3a04f57 26 days ago

Raw History Blame Contribute Delete

1.09 kB

name: CI Test Suite & Scientific Quality Gate

on:
  push:
    branches: [ main ]
  pull_request:
    branches: [ main ]

jobs:
  test:
    runs-on: ${{ matrix.os }}
    strategy:
      matrix:
        os: [ubuntu-latest, windows-latest, macos-latest]
        python-version: ["3.10", "3.11"]

    steps:
    - uses: actions/checkout@v4

    - name: Set up Python ${{ matrix.python-version }}
      uses: actions/setup-python@v5
      with:
        python-version: ${{ matrix.python-version }}

    - name: Install dependencies
      run: |
        python -m pip install --upgrade pip
        pip install -r requirements.txt
        pip install pytest
    - name: 1. Run Unit Test Suite (94 Tests)
      run: |
        python -m pytest -v
    - name: 2. Run Deterministic End-to-End Smoke Test
      run: |
        python scripts/smoke_test.py
    - name: 3. Run Automated Scientific Integrity Checker
      run: |
        python scripts/scientific_integrity_checker.py
    - name: 4. Run Technical SEO & Discoverability Quality Gate
      run: |
        python scripts/seo_audit.py

	name: CI Test Suite & Scientific Quality Gate

	on:
	push:
	branches: [ main ]
	pull_request:
	branches: [ main ]

	jobs:
	test:
	runs-on: ${{ matrix.os }}
	strategy:
	matrix:
	os: [ubuntu-latest, windows-latest, macos-latest]
	python-version: ["3.10", "3.11"]

	steps:
	- uses: actions/checkout@v4

	- name: Set up Python ${{ matrix.python-version }}
	uses: actions/setup-python@v5
	with:
	python-version: ${{ matrix.python-version }}

	- name: Install dependencies
	run: \|
	python -m pip install --upgrade pip
	pip install -r requirements.txt
	pip install pytest

	- name: 1. Run Unit Test Suite (94 Tests)
	run: \|
	python -m pytest -v

	- name: 2. Run Deterministic End-to-End Smoke Test
	run: \|
	python scripts/smoke_test.py

	- name: 3. Run Automated Scientific Integrity Checker
	run: \|
	python scripts/scientific_integrity_checker.py

	- name: 4. Run Technical SEO & Discoverability Quality Gate
	run: \|
	python scripts/seo_audit.py