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")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("diffutron/DiffutronLM-0.3B-Instruct", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

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/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "diffutron/DiffutronLM-0.3B-Instruct",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "diffutron/DiffutronLM-0.3B-Instruct",
		"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 "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/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "diffutron/DiffutronLM-0.3B-Instruct",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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

File size: 1,214 Bytes

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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
}