Instructions to use AngelRaychev/0.5B-value-iteration_5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AngelRaychev/0.5B-value-iteration_5 with Transformers:

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

pipe = pipeline("text-generation", model="AngelRaychev/0.5B-value-iteration_5")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("AngelRaychev/0.5B-value-iteration_5")
model = AutoModelForCausalLM.from_pretrained("AngelRaychev/0.5B-value-iteration_5")
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 AngelRaychev/0.5B-value-iteration_5 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "AngelRaychev/0.5B-value-iteration_5"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AngelRaychev/0.5B-value-iteration_5",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/AngelRaychev/0.5B-value-iteration_5

SGLang

How to use AngelRaychev/0.5B-value-iteration_5 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 "AngelRaychev/0.5B-value-iteration_5" \
    --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": "AngelRaychev/0.5B-value-iteration_5",
		"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 "AngelRaychev/0.5B-value-iteration_5" \
        --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": "AngelRaychev/0.5B-value-iteration_5",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use AngelRaychev/0.5B-value-iteration_5 with Docker Model Runner:
```
docker model run hf.co/AngelRaychev/0.5B-value-iteration_5
```

AngelRaychev commited on May 14, 2025

Commit

16607ae

verified ·

1 Parent(s): 4b1ca3f

Upload Qwen2ForCausalLM

Browse files

Files changed (2) hide show

config.json +1 -0
model.safetensors +1 -1

config.json CHANGED Viewed

@@ -11,6 +11,7 @@
   "intermediate_size": 4864,
   "max_position_embeddings": 32768,
   "max_window_layers": 24,
   "model_type": "qwen2",
   "num_attention_heads": 14,
   "num_hidden_layers": 24,

   "intermediate_size": 4864,
   "max_position_embeddings": 32768,
   "max_window_layers": 24,
+  "model_card": "\nFinal Loss: 0.2668\nBatch Size: 1024\nLearning Rate: 1e-05\nDataset Size: 167880\n",
   "model_type": "qwen2",
   "num_attention_heads": 14,
   "num_hidden_layers": 24,

model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:adbb0fa47b9e2358dba7f27c4a6ff4fa62436ec5477e463eeba880d019189ae0
 size 988097824

 version https://git-lfs.github.com/spec/v1
+oid sha256:1cf01546bfa5a10e99d6a5086c699f77b335dc924146ab23d6b3ea8a1a0c5275
 size 988097824