Instructions to use AlexandrosChariton/SarcasMLL-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlexandrosChariton/SarcasMLL-1B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="AlexandrosChariton/SarcasMLL-1B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("AlexandrosChariton/SarcasMLL-1B") model = AutoModelForCausalLM.from_pretrained("AlexandrosChariton/SarcasMLL-1B") 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]:])) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use AlexandrosChariton/SarcasMLL-1B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AlexandrosChariton/SarcasMLL-1B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AlexandrosChariton/SarcasMLL-1B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/AlexandrosChariton/SarcasMLL-1B
- SGLang
How to use AlexandrosChariton/SarcasMLL-1B 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 "AlexandrosChariton/SarcasMLL-1B" \ --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": "AlexandrosChariton/SarcasMLL-1B", "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 "AlexandrosChariton/SarcasMLL-1B" \ --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": "AlexandrosChariton/SarcasMLL-1B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use AlexandrosChariton/SarcasMLL-1B with Docker Model Runner:
docker model run hf.co/AlexandrosChariton/SarcasMLL-1B
This is a glorious and graceful gift to the open-source community from PyThess meetups, with love. It’s designed to provide sarcastic non-answers. Use with caution, and don’t trust it. Do not use it seriously—or at all. Do not expect it to qualify as a “helpful assistant.”
Built on top of Llama-3.2-1B-Instruct
Fine tuned with a dataset with sarcastic short "answers" to questions.
To test:
import torch
from transformers import pipeline
pipe = pipeline(
"text-generation",
model="AlexandrosChariton/SarcasMLL-1B",
torch_dtype=torch.float32,
device_map="auto",
)
messages = [
{"role": "user", "content": "Why do I even bother with Python? Is it any good?"},
]
outputs = pipe(
messages,
max_new_tokens=128
)
print(outputs[0]["generated_text"][-1])
Example input:
"Should I move to Scandinavia?"
Response:
{'role': 'assistant', 'content': "Oh yes, because nothing says 'good life' like freezing your butt off. And the cost of living? A whole other story. You might even need a warm coat. Worth a shot? Probably not. Scandinavia is all about embracing the cold. You'll love it. You'll hate it. Either way, you'll be fine. Or not. Who knows. It's all part of the adventure. Right?"}
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