Instructions to use SmallScale/Simple-Stories-Hindi-10M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SmallScale/Simple-Stories-Hindi-10M with Transformers:

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

pipe = pipeline("text-generation", model="SmallScale/Simple-Stories-Hindi-10M", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("SmallScale/Simple-Stories-Hindi-10M", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use SmallScale/Simple-Stories-Hindi-10M with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "SmallScale/Simple-Stories-Hindi-10M"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SmallScale/Simple-Stories-Hindi-10M",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/SmallScale/Simple-Stories-Hindi-10M

SGLang

How to use SmallScale/Simple-Stories-Hindi-10M 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 "SmallScale/Simple-Stories-Hindi-10M" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SmallScale/Simple-Stories-Hindi-10M",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "SmallScale/Simple-Stories-Hindi-10M" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SmallScale/Simple-Stories-Hindi-10M",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use SmallScale/Simple-Stories-Hindi-10M with Docker Model Runner:
```
docker model run hf.co/SmallScale/Simple-Stories-Hindi-10M
```

Simple-Stories-Hindi-10M / config.json

kaushik-harsh-99

Upload exported SimpleStories Hindi 10M/11M model with safetensors, custom modeling.py and tokenizer

70c8597 verified 1 day ago

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	{
	"architectures": [
	"SimpleStoriesForCausalLM"
	],
	"model_type": "simple_stories",
	"auto_map": {
	"AutoConfig": "modeling_simple_stories.SimpleStoriesConfig",
	"AutoModelForCausalLM": "modeling_simple_stories.SimpleStoriesForCausalLM"
	},
	"vocab_size": 4000,
	"max_seq_len": 512,
	"d_model": 320,
	"n_layers": 7,
	"n_heads": 5,
	"multiple_of": 64,
	"norm_eps": 1e-05,
	"dropout": 0.0,
	"bos_token_id": 2,
	"eos_token_id": 3,
	"pad_token_id": 0,
	"unk_token_id": 1,
	"torch_dtype": "float32"
	}