Instructions to use Sashvat/HQQ-270M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Sashvat/HQQ-270M with Transformers:

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

pipe = pipeline("text-generation", model="Sashvat/HQQ-270M")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Sashvat/HQQ-270M")
model = AutoModelForCausalLM.from_pretrained("Sashvat/HQQ-270M")
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 Sashvat/HQQ-270M with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Sashvat/HQQ-270M"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Sashvat/HQQ-270M",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Sashvat/HQQ-270M

SGLang

How to use Sashvat/HQQ-270M 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 "Sashvat/HQQ-270M" \
    --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": "Sashvat/HQQ-270M",
		"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 "Sashvat/HQQ-270M" \
        --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": "Sashvat/HQQ-270M",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Sashvat/HQQ-270M with Docker Model Runner:
```
docker model run hf.co/Sashvat/HQQ-270M
```

Akshat-Dwivedi commited on Mar 29

Commit

38ef32f

verified ·

1 Parent(s): 9367810

Update LICENSE

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@@ -1,14 +1,14 @@
-Nukeverse AI License v1.0
-Permission is hereby granted to use, copy, modify, and distribute this model and derivative works for any purpose, including commercial use, provided that proper attribution is given.
-Attribution Requirement:
-Any use, redistribution, or derivative of this model must include a clear and visible attribution statement:
-"Made by Nukeverse AI"
-This attribution must appear in any papers, blog posts, apps, services, or other works that use the model or its derivatives.
-Disclaimer:
-This model is provided "as is" without warranties of any kind, express or implied.
-Nukeverse AI shall not be held liable for any damages arising from the use of this model.

+Sashvat AI License v1.0
+Permission is hereby granted to use, copy, modify, and distribute this model and derivative works for any purpose, including commercial use, provided that proper attribution is given.
+Attribution Requirement:
+Any use, redistribution, or derivative of this model must include a clear and visible attribution statement:
+"Made by Sashvat AI"
+This attribution must appear in any papers, blog posts, apps, services, or other works that use the model or its derivatives.
+Disclaimer:
+This model is provided "as is" without warranties of any kind, express or implied.
+Sashvat AI shall not be held liable for any damages arising from the use of this model.