Instructions to use InfinimindCreations/Spark-X2.5-4B-uncensored with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use InfinimindCreations/Spark-X2.5-4B-uncensored with Transformers:

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

pipe = pipeline("text-generation", model="InfinimindCreations/Spark-X2.5-4B-uncensored", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("InfinimindCreations/Spark-X2.5-4B-uncensored", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use InfinimindCreations/Spark-X2.5-4B-uncensored with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "InfinimindCreations/Spark-X2.5-4B-uncensored"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "InfinimindCreations/Spark-X2.5-4B-uncensored",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/InfinimindCreations/Spark-X2.5-4B-uncensored

SGLang

How to use InfinimindCreations/Spark-X2.5-4B-uncensored 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 "InfinimindCreations/Spark-X2.5-4B-uncensored" \
    --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": "InfinimindCreations/Spark-X2.5-4B-uncensored",
		"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 "InfinimindCreations/Spark-X2.5-4B-uncensored" \
        --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": "InfinimindCreations/Spark-X2.5-4B-uncensored",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use InfinimindCreations/Spark-X2.5-4B-uncensored with Docker Model Runner:
```
docker model run hf.co/InfinimindCreations/Spark-X2.5-4B-uncensored
```

Cytrex commited on 24 days ago

Commit

3ca3a2e

verified ·

1 Parent(s): 97e6c31

Upload config.json with huggingface_hub

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config.json +85 -0

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	@@ -0,0 +1,85 @@

+{
+  "architectures": [
+    "Spark2_5ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "auto_map": {
+    "AutoConfig": "configuration_spark.Spark2_5Config",
+    "AutoModel": "modeling_spark.Spark2_5Model",
+    "AutoModelForCausalLM": "modeling_spark.Spark2_5ForCausalLM"
+  },
+  "bos_token_id": 0,
+  "dtype": "bfloat16",
+  "eos_token_id": 1,
+  "gate_attn_act_mode": "sigmoid",
+  "head_dim": 256,
+  "headwise_attn_output_gate": true,
+  "hidden_act": "gelu",
+  "hidden_size": 2560,
+  "initializer_range": 0.01976,
+  "intermediate_size": 10240,
+  "layer_types": [
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 1048576,
+  "mlp_bias": false,
+  "model_type": "spark2_5",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 36,
+  "num_key_value_heads": 4,
+  "pad_token_id": 2,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "full_attention": {
+      "partial_rotary_factor": 0.25,
+      "rope_theta": 5000000
+    },
+    "rope_theta": 10000.0,
+    "rope_type": "default",
+    "sliding_attention": {
+      "partial_rotary_factor": 1.0,
+      "rope_theta": 10000
+    }
+  },
+  "sliding_window": 512,
+  "tie_word_embeddings": true,
+  "transformers_version": "5.16.1",
+  "use_cache": true,
+  "vocab_size": 131072
+}