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: 1,512 Bytes

38b4eff

<?php

declare(strict_types=1);

/**
 * SPDX-FileCopyrightText: 2016 Nextcloud GmbH and Nextcloud contributors
 * SPDX-License-Identifier: AGPL-3.0-or-later
 */
namespace OC\Core\Migrations;

use Closure;
use OCP\DB\ISchemaWrapper;
use OCP\Migration\IOutput;
use OCP\Migration\SimpleMigrationStep;

class Version21000Date20201120141228 extends SimpleMigrationStep {
	public function changeSchema(IOutput $output, Closure $schemaClosure, array $options): ?ISchemaWrapper {
		/** @var ISchemaWrapper $schema */
		$schema = $schemaClosure();

		if ($schema->hasTable('authtoken')) {
			$table = $schema->getTable('authtoken');
			$loginNameColumn = $table->getColumn('login_name');
			if ($loginNameColumn->getLength() !== 255) {
				$loginNameColumn->setLength(255);
			}
			$table->modifyColumn('type', [
				'notnull' => false,
			]);
			$table->modifyColumn('remember', [
				'notnull' => false,
			]);
			$table->modifyColumn('last_activity', [
				'notnull' => false,
			]);
			$table->modifyColumn('last_check', [
				'notnull' => false,
			]);
		}

		if ($schema->hasTable('dav_job_status')) {
			$schema->dropTable('dav_job_status');
		}

		if ($schema->hasTable('share')) {
			$table = $schema->getTable('share');
			if ($table->hasColumn('attributes')) {
				$table->dropColumn('attributes');
			}
		}

		if ($schema->hasTable('jobs')) {
			$table = $schema->getTable('jobs');
			$table->modifyColumn('execution_duration', [
				'notnull' => false,
				'default' => 0,
			]);
		}

		return $schema;
	}
}