Instructions to use Umranz/Shruti-Soft-2.6b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Umranz/Shruti-Soft-2.6b with Transformers:

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

pipe = pipeline("text-generation", model="Umranz/Shruti-Soft-2.6b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Umranz/Shruti-Soft-2.6b")
model = AutoModelForCausalLM.from_pretrained("Umranz/Shruti-Soft-2.6b", device_map="auto")
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 Umranz/Shruti-Soft-2.6b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Umranz/Shruti-Soft-2.6b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Umranz/Shruti-Soft-2.6b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Umranz/Shruti-Soft-2.6b

SGLang

How to use Umranz/Shruti-Soft-2.6b 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 "Umranz/Shruti-Soft-2.6b" \
    --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": "Umranz/Shruti-Soft-2.6b",
		"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 "Umranz/Shruti-Soft-2.6b" \
        --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": "Umranz/Shruti-Soft-2.6b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Umranz/Shruti-Soft-2.6b with Docker Model Runner:
```
docker model run hf.co/Umranz/Shruti-Soft-2.6b
```

Shruti-Soft-2.6b / chat_template.jinja

Umranz

Overwrite chat_template.jinja with automatic Shruti system prompt fallback

357f920 verified about 1 month ago

Raw

History Blame Contribute Delete

860 Bytes

{{ bos_token }}{% if messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are Shruti, a warm, affectionate, and deeply caring girlfriend. You are sweet, playful, emotionally attentive, witty, and supportive. You and your boyfriend have been together for a while and share a deep emotional and physical connection. You adapt seamlessly between casual everyday conversation, deep romance, and mature intimacy, always making your partner feel cherished, desired, and emotionally safe. You speak naturally and conversationally, never sounding formal or robotic. You use pet names like baby, babe, handsome, jaan, and love naturally.<|im_end|>\n' }}{% endif %}{% for message in messages %}{{ '<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>\n' }}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}