Instructions to use gumran/distilbert-diffusion-TinyStories with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use gumran/distilbert-diffusion-TinyStories with Transformers:

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

pipe = pipeline("text-generation", model="gumran/distilbert-diffusion-TinyStories")

# Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM

tokenizer = AutoTokenizer.from_pretrained("gumran/distilbert-diffusion-TinyStories")
model = AutoModelForMaskedLM.from_pretrained("gumran/distilbert-diffusion-TinyStories")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use gumran/distilbert-diffusion-TinyStories with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/gumran/distilbert-diffusion-TinyStories

SGLang

How to use gumran/distilbert-diffusion-TinyStories 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 "gumran/distilbert-diffusion-TinyStories" \
    --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": "gumran/distilbert-diffusion-TinyStories",
		"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 "gumran/distilbert-diffusion-TinyStories" \
        --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": "gumran/distilbert-diffusion-TinyStories",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use gumran/distilbert-diffusion-TinyStories with Docker Model Runner:
```
docker model run hf.co/gumran/distilbert-diffusion-TinyStories
```

distilbert-diffusion-TinyStories / config.json

gumran

Upload DistilBertForMaskedLM

99740f4 verified 10 months ago

Raw

History Blame Contribute Delete

529 Bytes

	{
	"activation": "gelu",
	"architectures": [
	"DistilBertForMaskedLM"
	],
	"attention_dropout": 0.1,
	"dim": 768,
	"dropout": 0.1,
	"hidden_dim": 3072,
	"initializer_range": 0.02,
	"max_position_embeddings": 512,
	"model_type": "distilbert",
	"n_heads": 12,
	"n_layers": 6,
	"output_past": true,
	"pad_token_id": 0,
	"qa_dropout": 0.1,
	"seq_classif_dropout": 0.2,
	"sinusoidal_pos_embds": false,
	"tie_weights_": true,
	"torch_dtype": "float32",
	"transformers_version": "4.52.4",
	"vocab_size": 28996
	}