Instructions to use SingularityPrinciple/DiffusionGemma-26B-A4B-it-Infinite-Context with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SingularityPrinciple/DiffusionGemma-26B-A4B-it-Infinite-Context with Transformers:

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

pipe = pipeline("image-text-to-text", model="SingularityPrinciple/DiffusionGemma-26B-A4B-it-Infinite-Context")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("SingularityPrinciple/DiffusionGemma-26B-A4B-it-Infinite-Context", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use SingularityPrinciple/DiffusionGemma-26B-A4B-it-Infinite-Context with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "SingularityPrinciple/DiffusionGemma-26B-A4B-it-Infinite-Context"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SingularityPrinciple/DiffusionGemma-26B-A4B-it-Infinite-Context",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/SingularityPrinciple/DiffusionGemma-26B-A4B-it-Infinite-Context

SGLang

How to use SingularityPrinciple/DiffusionGemma-26B-A4B-it-Infinite-Context 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 "SingularityPrinciple/DiffusionGemma-26B-A4B-it-Infinite-Context" \
    --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": "SingularityPrinciple/DiffusionGemma-26B-A4B-it-Infinite-Context",
		"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 "SingularityPrinciple/DiffusionGemma-26B-A4B-it-Infinite-Context" \
        --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": "SingularityPrinciple/DiffusionGemma-26B-A4B-it-Infinite-Context",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use SingularityPrinciple/DiffusionGemma-26B-A4B-it-Infinite-Context with Docker Model Runner:
```
docker model run hf.co/SingularityPrinciple/DiffusionGemma-26B-A4B-it-Infinite-Context
```

DiffusionGemma-26B-A4B-it-Infinite-Context / examples /optional_diffusiongemma_model_load_check.py

SingularityPrinciple

Fix validation and example script import paths

f77c1f2 verified 8 days ago

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1.2 kB

	import sys
	from pathlib import Path

	ROOT = Path(__file__).resolve().parents[1]
	if str(ROOT) not in sys.path:
	sys.path.insert(0, str(ROOT))

	import os

	from nzfc_gram_runtime import NZFCGramLongMemoryChat
	from nzfc_gram_runtime.quality import attach_answer_quality_governor
	from nzfc_gram_runtime.large_document import attach_large_document_memory
	from nzfc_gram_runtime.diffusiongemma_adapter import attach_diffusiongemma_block_diffusion

	MODEL_ID = 'google/diffusiongemma-26B-A4B-it'

	if os.environ.get('LOAD_MODEL', '0') != '1':
	print('Set LOAD_MODEL=1 to run this optional model-load check.')
	raise SystemExit(0)

	bot = NZFCGramLongMemoryChat(
	repo_dir=str(ROOT),
	model_id=MODEL_ID,
	memory_db_path='./optional_model_load_memory.sqlite3',
	load_model=False,
	require_model=False,
	preload_static_memory=False,
	)

	attach_large_document_memory(bot)
	attach_answer_quality_governor(bot)

	meta = attach_diffusiongemma_block_diffusion(
	bot,
	model_id=MODEL_ID,
	device_map='auto',
	dtype='auto',
	)

	print(meta)

	out = bot.generate_answer(
	system_prompt='You are concise.',
	user_prompt='Say DIFFUSIONGEMMA_OK.',
	max_new_tokens=32,
	)

	print(out)