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

Libraries

How to use elementalsouls/ArcNemesis with Transformers:

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

pipe = pipeline("text-generation", model="elementalsouls/ArcNemesis")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("elementalsouls/ArcNemesis")
model = AutoModelForCausalLM.from_pretrained("elementalsouls/ArcNemesis")
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 elementalsouls/ArcNemesis with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/elementalsouls/ArcNemesis

SGLang

How to use elementalsouls/ArcNemesis 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 "elementalsouls/ArcNemesis" \
    --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": "elementalsouls/ArcNemesis",
		"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 "elementalsouls/ArcNemesis" \
        --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": "elementalsouls/ArcNemesis",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use elementalsouls/ArcNemesis with Docker Model Runner:
```
docker model run hf.co/elementalsouls/ArcNemesis
```

ArcNemesis

Commit History

Upload tokenizer

d1ba4b6
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Sachin Sharma commited on May 29, 2025

Upload MistralForCausalLM

8396011
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Sachin Sharma commited on May 29, 2025

initial commit

c7647bb
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Sachin Sharma commited on May 29, 2025

Commit History

Upload tokenizer d1ba4b6 verified

Upload MistralForCausalLM 8396011 verified

initial commit c7647bb verified

Upload tokenizer

d1ba4b6
verified

Upload MistralForCausalLM

8396011
verified

initial commit

c7647bb
verified