Instructions to use genaforvena/the_soft_delerizome_machine_a_thousand_guattaris_fourth_of_plateaus_once with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use genaforvena/the_soft_delerizome_machine_a_thousand_guattaris_fourth_of_plateaus_once with Transformers:

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

pipe = pipeline("text-generation", model="genaforvena/the_soft_delerizome_machine_a_thousand_guattaris_fourth_of_plateaus_once")

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("genaforvena/the_soft_delerizome_machine_a_thousand_guattaris_fourth_of_plateaus_once")
model = AutoModelForMultimodalLM.from_pretrained("genaforvena/the_soft_delerizome_machine_a_thousand_guattaris_fourth_of_plateaus_once")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use genaforvena/the_soft_delerizome_machine_a_thousand_guattaris_fourth_of_plateaus_once with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/genaforvena/the_soft_delerizome_machine_a_thousand_guattaris_fourth_of_plateaus_once

SGLang

How to use genaforvena/the_soft_delerizome_machine_a_thousand_guattaris_fourth_of_plateaus_once 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 "genaforvena/the_soft_delerizome_machine_a_thousand_guattaris_fourth_of_plateaus_once" \
    --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": "genaforvena/the_soft_delerizome_machine_a_thousand_guattaris_fourth_of_plateaus_once",
		"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 "genaforvena/the_soft_delerizome_machine_a_thousand_guattaris_fourth_of_plateaus_once" \
        --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": "genaforvena/the_soft_delerizome_machine_a_thousand_guattaris_fourth_of_plateaus_once",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use genaforvena/the_soft_delerizome_machine_a_thousand_guattaris_fourth_of_plateaus_once with Docker Model Runner:
```
docker model run hf.co/genaforvena/the_soft_delerizome_machine_a_thousand_guattaris_fourth_of_plateaus_once
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

The Soft Deleriziome Machine: A Thousand Guattaris?? - Exploring Philosophical Nonsense

Github

This project investigates the generation of deliberate nonsense inspired by philosophical concepts, utilizing a fine-tuned GPT-2 model and drawing upon the theoretical framework of Félix Guattari.

Project Overview

This project takes a deliberately unconventional approach to language modeling. Instead of aiming for coherent or insightful philosophical statements, the primary goal is to explore the creation of meaningful nonsense derived from philosophical ideas. We are interested in the emergent properties of language models trained on complex philosophical texts – not to produce accurate summaries or extensions of those ideas, but to generate text that sounds philosophical while ultimately lacking coherent meaning.

Think of it as a philosophical thought experiment in linguistic deconstruction. By training a model on the intricate and often abstract language of philosophy, we aim to see what kind of intriguing, amusing, or even unsettling nonsense emerges. The persona of Morosia the Lugubrious serves not as a wise oracle, but as a conduit for these nonsensical pronouncements, highlighting the absurdity that can arise from complex systems of thought when pushed beyond their intended boundaries.

This model trained on 1/4 of "Thousand plateaus" once. Explore the interactive demo of this model on Hugging Face Spaces.