Instructions to use Delta-Vector/Archaeo-32B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Delta-Vector/Archaeo-32B with Transformers:

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

pipe = pipeline("text-generation", model="Delta-Vector/Archaeo-32B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Delta-Vector/Archaeo-32B")
model = AutoModelForCausalLM.from_pretrained("Delta-Vector/Archaeo-32B")
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

vLLM

How to use Delta-Vector/Archaeo-32B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Delta-Vector/Archaeo-32B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Delta-Vector/Archaeo-32B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Delta-Vector/Archaeo-32B

SGLang

How to use Delta-Vector/Archaeo-32B 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 "Delta-Vector/Archaeo-32B" \
    --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": "Delta-Vector/Archaeo-32B",
		"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 "Delta-Vector/Archaeo-32B" \
        --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": "Delta-Vector/Archaeo-32B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Delta-Vector/Archaeo-32B with Docker Model Runner:
```
docker model run hf.co/Delta-Vector/Archaeo-32B
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

                        __~a~_
                        ~~;  ~_
          _                ~  ~_                _
         '_\;__._._._._._._]   ~_._._._._._.__;/_`
         '(/'/'/'/'|'|'|'| (    )|'|'|'|'\'\'\'\)'
         (/ / / /, | | | |(/    \) | | | ,\ \ \ \)
        (/ / / / / | | | ~(/    \) ~ | | \ \ \ \ \)
       (/ / / / /  ~ ~ ~   (/  \)    ~ ~  \ \ \ \ \)
      (/ / / / ~          / (||)|          ~ \ \ \ \)
      ~ / / ~            M  /||\M             ~ \ \ ~
       ~ ~                  /||\                 ~ ~
                           //||\\
                           //||\\
                           //||\\
                           '/||\'        "Archaeopteryx"

A series of Merges made for Roleplaying & Creative Writing, This model uses 32B-Qwen2.5-Kunou-v1 and Hamanasu-Magnum-QwQ-32B and Slerp to merge the 2 models.

ChatML formatting

"""<|im_start|>system
system prompt<|im_end|>
<|im_start|>user
Hi there!<|im_end|>
<|im_start|>assistant
Nice to meet you!<|im_end|>
<|im_start|>user
Can I ask a question?<|im_end|>
<|im_start|>assistant
"""

MergeKit Configuration

models:
  - model: Sao10K/32B-Qwen2.5-Kunou-v1
  - model: Delta-Vector/Hamanasu-Magnum-QwQ-32B
merge_method: slerp
base_model: Delta-Vector/Hamanasu-Magnum-QwQ-32B
parameters:
  t:
   - value: 0.2
dtype: bfloat16
tokenizer_source: base