Instructions to use Subject-Emu-5259/NeuralAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries
PEFT
How to use Subject-Emu-5259/NeuralAI with PEFT:
```
Base model is not found.
```

How to use Subject-Emu-5259/NeuralAI with Transformers:

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

pipe = pipeline("text-generation", model="Subject-Emu-5259/NeuralAI", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Subject-Emu-5259/NeuralAI")
model = AutoModelForCausalLM.from_pretrained("Subject-Emu-5259/NeuralAI", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Subject-Emu-5259/NeuralAI with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Subject-Emu-5259/NeuralAI"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Subject-Emu-5259/NeuralAI",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Subject-Emu-5259/NeuralAI

SGLang

How to use Subject-Emu-5259/NeuralAI 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 "Subject-Emu-5259/NeuralAI" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Subject-Emu-5259/NeuralAI",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "Subject-Emu-5259/NeuralAI" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Subject-Emu-5259/NeuralAI",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Subject-Emu-5259/NeuralAI with Docker Model Runner:
```
docker model run hf.co/Subject-Emu-5259/NeuralAI
```

NeuralAI

File size: 1,490 Bytes

38b4eff

<?php

declare(strict_types=1);

/**
 * SPDX-FileCopyrightText: 2016-2024 Nextcloud GmbH and Nextcloud contributors
 * SPDX-FileCopyrightText: 2016 ownCloud, Inc.
 * SPDX-License-Identifier: AGPL-3.0-only
 */

require_once __DIR__ . '/lib/versioncheck.php';

use OC\SystemConfig;
use OCP\Defaults;
use OCP\Server;
use OCP\ServerVersion;
use OCP\Util;
use Psr\Log\LoggerInterface;

try {
	require_once __DIR__ . '/lib/base.php';

	$systemConfig = Server::get(SystemConfig::class);

	$installed = (bool)$systemConfig->getValue('installed', false);
	$maintenance = (bool)$systemConfig->getValue('maintenance', false);
	# see core/lib/private/legacy/defaults.php and core/themes/example/defaults.php
	# for description and defaults
	$defaults = new Defaults();
	$serverVersion = Server::get(ServerVersion::class);
	$values = [
		'installed' => $installed,
		'maintenance' => $maintenance,
		'needsDbUpgrade' => Util::needUpgrade(),
		'version' => implode('.', $serverVersion->getVersion()),
		'versionstring' => $serverVersion->getVersionString(),
		'edition' => '',
		'productname' => $defaults->getProductName(),
		'extendedSupport' => Util::hasExtendedSupport()
	];
	if (OC::$CLI) {
		print_r($values);
	} else {
		header('Access-Control-Allow-Origin: *');
		header('Content-Type: application/json');
		echo json_encode($values);
	}
} catch (Exception $ex) {
	http_response_code(500);
	Server::get(LoggerInterface::class)->error($ex->getMessage(), ['app' => 'remote','exception' => $ex]);
}