Instructions to use HenrySentinel/tinyMind with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use HenrySentinel/tinyMind with Transformers:

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

pipe = pipeline("text-generation", model="HenrySentinel/tinyMind", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("HenrySentinel/tinyMind", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use HenrySentinel/tinyMind with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/HenrySentinel/tinyMind

SGLang

How to use HenrySentinel/tinyMind 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 "HenrySentinel/tinyMind" \
    --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": "HenrySentinel/tinyMind",
		"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 "HenrySentinel/tinyMind" \
        --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": "HenrySentinel/tinyMind",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use HenrySentinel/tinyMind with Docker Model Runner:
```
docker model run hf.co/HenrySentinel/tinyMind
```

HenrySentinel commited on 14 days ago

Commit

d35c72d

verified ·

1 Parent(s): 2f2a785

Update config with auto_map for trust_remote_code loading

Browse files

Files changed (1) hide show

config.json +13 -4

config.json CHANGED Viewed

@@ -1,14 +1,23 @@
 {
-  "architectures": [
-    "TinySmartLLMForHF"
-  ],
   "dropout": 0.1,
   "max_seq_len": 512,
   "model_type": "tiny_smart_llm",
   "n_embd": 256,
   "n_heads": 8,
   "n_layers": 6,
   "torch_dtype": "float32",
   "transformers_version": "4.51.3",
-  "vocab_size": 50257
 }

 {
+  "architectures": ["TinyMindForCausalLM"],
+  "auto_map": {
+    "AutoConfig": "configuration_tinymind.TinyMindConfig",
+    "AutoModelForCausalLM": "modeling_tinymind.TinyMindForCausalLM"
+  },
   "dropout": 0.1,
   "max_seq_len": 512,
   "model_type": "tiny_smart_llm",
   "n_embd": 256,
   "n_heads": 8,
   "n_layers": 6,
+  "num_hidden_layers": 6,
+  "hidden_size": 256,
+  "num_attention_heads": 8,
+  "max_position_embeddings": 512,
   "torch_dtype": "float32",
   "transformers_version": "4.51.3",
+  "vocab_size": 50257,
+  "bos_token_id": 50256,
+  "eos_token_id": 50256,
+  "pad_token_id": 50256
 }