Instructions to use diffutron/DiffutronLM-0.3B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use diffutron/DiffutronLM-0.3B-Instruct with Transformers:

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

pipe = pipeline("text-generation", model="diffutron/DiffutronLM-0.3B-Instruct")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM

tokenizer = AutoTokenizer.from_pretrained("diffutron/DiffutronLM-0.3B-Instruct")
model = AutoModelForMaskedLM.from_pretrained("diffutron/DiffutronLM-0.3B-Instruct")
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 diffutron/DiffutronLM-0.3B-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "diffutron/DiffutronLM-0.3B-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "diffutron/DiffutronLM-0.3B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/diffutron/DiffutronLM-0.3B-Instruct

SGLang

How to use diffutron/DiffutronLM-0.3B-Instruct 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 "diffutron/DiffutronLM-0.3B-Instruct" \
    --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": "diffutron/DiffutronLM-0.3B-Instruct",
		"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 "diffutron/DiffutronLM-0.3B-Instruct" \
        --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": "diffutron/DiffutronLM-0.3B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use diffutron/DiffutronLM-0.3B-Instruct with Docker Model Runner:
```
docker model run hf.co/diffutron/DiffutronLM-0.3B-Instruct
```

DiffutronLM-0.3B-Instruct / config.json

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	{
	"architectures": [
	"ModernBertForMaskedLM"
	],
	"attention_bias": false,
	"attention_dropout": 0.0,
	"bos_token_id": 2,
	"classifier_activation": "gelu",
	"classifier_bias": false,
	"classifier_dropout": 0.0,
	"classifier_pooling": "mean",
	"cls_token_id": 1,
	"decoder_bias": true,
	"deterministic_flash_attn": false,
	"dtype": "float32",
	"embedding_dropout": 0.0,
	"eos_token_id": 1,
	"global_attn_every_n_layers": 3,
	"global_rope_theta": 160000,
	"gradient_checkpointing": false,
	"hidden_activation": "gelu",
	"hidden_size": 768,
	"initializer_cutoff_factor": 2.0,
	"initializer_range": 0.02,
	"intermediate_size": 1152,
	"layer_norm_eps": 1e-05,
	"local_attention": 128,
	"local_rope_theta": 160000,
	"mask_token_id": 4,
	"max_position_embeddings": 8192,
	"mlp_bias": false,
	"mlp_dropout": 0.0,
	"model_type": "modernbert",
	"norm_bias": false,
	"norm_eps": 1e-05,
	"num_attention_heads": 12,
	"num_hidden_layers": 22,
	"pad_token_id": 0,
	"position_embedding_type": "sans_pos",
	"repad_logits_with_grad": false,
	"sep_token_id": 1,
	"sparse_pred_ignore_index": -100,
	"sparse_prediction": false,
	"transformers_version": "4.57.0",
	"vocab_size": 256000
	}