Instructions to use Sim4Rec/inter-play-sim-assistant-sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Sim4Rec/inter-play-sim-assistant-sft with Transformers:

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

pipe = pipeline("text-generation", model="Sim4Rec/inter-play-sim-assistant-sft")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Sim4Rec/inter-play-sim-assistant-sft")
model = AutoModelForCausalLM.from_pretrained("Sim4Rec/inter-play-sim-assistant-sft")
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

vLLM

How to use Sim4Rec/inter-play-sim-assistant-sft with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Sim4Rec/inter-play-sim-assistant-sft"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Sim4Rec/inter-play-sim-assistant-sft",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Sim4Rec/inter-play-sim-assistant-sft

SGLang

How to use Sim4Rec/inter-play-sim-assistant-sft 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 "Sim4Rec/inter-play-sim-assistant-sft" \
    --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": "Sim4Rec/inter-play-sim-assistant-sft",
		"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 "Sim4Rec/inter-play-sim-assistant-sft" \
        --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": "Sim4Rec/inter-play-sim-assistant-sft",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Sim4Rec/inter-play-sim-assistant-sft with Docker Model Runner:
```
docker model run hf.co/Sim4Rec/inter-play-sim-assistant-sft
```

jeromeramos commited on Feb 2, 2025

Commit

104abb7

verified ·

1 Parent(s): c65e1e2

End of training

Browse files

Files changed (3) hide show

all_results.json +5 -0
eval_results.json +8 -0
runs/Feb02_00-04-32_w-jerom-inter-play-sim-94c6890b9ccf44ea86f033a3db8a5dbd-9crbrgc/events.out.tfevents.1738459710.w-jerom-inter-play-sim-94c6890b9ccf44ea86f033a3db8a5dbd-9crbrgc.24610.1 +3 -0

all_results.json CHANGED Viewed

@@ -1,5 +1,10 @@
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 {
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     "train_loss": 0.914938143180119,
     "train_runtime": 4445.7565,

eval_results.json ADDED Viewed

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

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+    "eval_runtime": 98.2909,
+    "eval_samples": 2071,
+    "eval_samples_per_second": 46.902,
+    "eval_steps_per_second": 2.94
+}

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