Instructions to use madox81/SmolLM2-Cyber-Insight-r64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use madox81/SmolLM2-Cyber-Insight-r64 with Transformers:

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

pipe = pipeline("text-generation", model="madox81/SmolLM2-Cyber-Insight-r64")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("madox81/SmolLM2-Cyber-Insight-r64")
model = AutoModelForCausalLM.from_pretrained("madox81/SmolLM2-Cyber-Insight-r64")
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 madox81/SmolLM2-Cyber-Insight-r64 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "madox81/SmolLM2-Cyber-Insight-r64"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "madox81/SmolLM2-Cyber-Insight-r64",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/madox81/SmolLM2-Cyber-Insight-r64

SGLang

How to use madox81/SmolLM2-Cyber-Insight-r64 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 "madox81/SmolLM2-Cyber-Insight-r64" \
    --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": "madox81/SmolLM2-Cyber-Insight-r64",
		"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 "madox81/SmolLM2-Cyber-Insight-r64" \
        --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": "madox81/SmolLM2-Cyber-Insight-r64",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Studio

How to use madox81/SmolLM2-Cyber-Insight-r64 with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for madox81/SmolLM2-Cyber-Insight-r64 to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for madox81/SmolLM2-Cyber-Insight-r64 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for madox81/SmolLM2-Cyber-Insight-r64 to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="madox81/SmolLM2-Cyber-Insight-r64",
    max_seq_length=2048,
)

Docker Model Runner
How to use madox81/SmolLM2-Cyber-Insight-r64 with Docker Model Runner:
```
docker model run hf.co/madox81/SmolLM2-Cyber-Insight-r64
```

madox81 commited on Apr 3

Commit

bf7f319

verified ·

1 Parent(s): 149f358

(Trained with Unsloth)

Browse files

Files changed (4) hide show

chat_template.jinja +8 -0
config.json +32 -0
tokenizer.json +0 -0
tokenizer_config.json +10 -0

chat_template.jinja ADDED Viewed

	@@ -0,0 +1,8 @@

+{% for message in messages %}{% if message['role'] == 'user' %}{{'<|im_start|>user
+' + message['content'] + '<|im_end|>
+'}}{% elif message['role'] == 'assistant' %}{{'<|im_start|>assistant
+' + message['content'] + '<|im_end|>
+' }}{% else %}{{ '<|im_start|>system
+' + message['content'] + '<|im_end|>
+' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
+' }}{% endif %}

config.json ADDED Viewed

	@@ -0,0 +1,32 @@

+{
+    "architectures": [
+        "LlamaForCausalLM"
+    ],
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "bos_token_id": 2,
+    "torch_dtype": "float16",
+    "eos_token_id": 0,
+    "head_dim": 64,
+    "hidden_act": "silu",
+    "hidden_size": 2048,
+    "initializer_range": 0.02,
+    "intermediate_size": 8192,
+    "max_position_embeddings": 8192,
+    "mlp_bias": false,
+    "model_type": "llama",
+    "num_attention_heads": 32,
+    "num_hidden_layers": 24,
+    "num_key_value_heads": 32,
+    "pad_token_id": 2,
+    "pretraining_tp": 1,
+    "rms_norm_eps": 1e-05,
+    "rope_parameters": {
+        "rope_theta": 130000,
+        "rope_type": "default"
+    },
+    "tie_word_embeddings": true,
+    "unsloth_version": "2026.4.1",
+    "use_cache": false,
+    "vocab_size": 49152
+}

tokenizer.json ADDED Viewed

The diff for this file is too large to render. See raw diff

tokenizer_config.json ADDED Viewed

	@@ -0,0 +1,10 @@

+{
+  "backend": "tokenizers",
+  "bos_token": "<|endoftext|>",
+  "eos_token": "<|im_end|>",
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<|endoftext|>",
+  "tokenizer_class": "TokenizersBackend",
+  "unk_token": "<|endoftext|>",
+  "chat_template": "{% for message in messages %}{% if message['role'] == 'user' %}{{'<|im_start|>user\n' + message['content'] + '<|im_end|>\n'}}{% elif message['role'] == 'assistant' %}{{'<|im_start|>assistant\n' + message['content'] + '<|im_end|>\n' }}{% else %}{{ '<|im_start|>system\n' + message['content'] + '<|im_end|>\n' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}"
+}