Instructions to use EpistemeAI/ReasoningCore-3B-R01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use EpistemeAI/ReasoningCore-3B-R01 with Transformers:

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

pipe = pipeline("text-generation", model="EpistemeAI/ReasoningCore-3B-R01")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("EpistemeAI/ReasoningCore-3B-R01")
model = AutoModelForCausalLM.from_pretrained("EpistemeAI/ReasoningCore-3B-R01", device_map="auto")
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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use EpistemeAI/ReasoningCore-3B-R01 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "EpistemeAI/ReasoningCore-3B-R01"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "EpistemeAI/ReasoningCore-3B-R01",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/EpistemeAI/ReasoningCore-3B-R01

SGLang

How to use EpistemeAI/ReasoningCore-3B-R01 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 "EpistemeAI/ReasoningCore-3B-R01" \
    --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": "EpistemeAI/ReasoningCore-3B-R01",
		"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 "EpistemeAI/ReasoningCore-3B-R01" \
        --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": "EpistemeAI/ReasoningCore-3B-R01",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Studio

How to use EpistemeAI/ReasoningCore-3B-R01 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 EpistemeAI/ReasoningCore-3B-R01 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 EpistemeAI/ReasoningCore-3B-R01 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for EpistemeAI/ReasoningCore-3B-R01 to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="EpistemeAI/ReasoningCore-3B-R01",
    max_seq_length=2048,
)

Docker Model Runner
How to use EpistemeAI/ReasoningCore-3B-R01 with Docker Model Runner:
```
docker model run hf.co/EpistemeAI/ReasoningCore-3B-R01
```

legolasyiu commited on Aug 29, 2025

Commit

748d84b

verified ·

1 Parent(s): a9306ca

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@@ -166,14 +166,14 @@ For further details, questions, or feedback, please email episteme.ai@proton.me
 ## Benchmark
-hf (pretrained=EpistemeAI/ReasoningCore-3B-R01), gen_kwargs: (None), limit: None, num_fewshot: 1, batch_size: 8
 |    Tasks    |Version|Filter|n-shot| Metric |   |Value |   |Stderr|
 |-------------|------:|------|-----:|--------|---|-----:|---|-----:|
-|arc_challenge|      1|none  |     1|acc     |↑  |0.4113|±  |0.0144|
-|             |       |none  |     1|acc_norm|↑  |0.4548|±  |0.0146|
-|hellaswag    |      1|none  |     1|acc     |↑  |0.5103|±  |0.0050|
-|             |       |none  |     1|acc_norm|↑  |0.6965|±  |0.0046|
-|winogrande   |      1|none  |     1|acc     |↑  |0.6654|±  |0.0133|
 # Uploaded  model

 ## Benchmark
+hf (pretrained=EpistemeAI/ReasoningCore-3B-R01), gen_kwargs: (None), limit: None, num_fewshot: 5, batch_size: 8
 |    Tasks    |Version|Filter|n-shot| Metric |   |Value |   |Stderr|
 |-------------|------:|------|-----:|--------|---|-----:|---|-----:|
+|arc_challenge|      1|none  |     5|acc     |↑  |0.4352|±  |0.0145|
+|             |       |none  |     5|acc_norm|↑  |0.4889|±  |0.0146|
+|hellaswag    |      1|none  |     5|acc     |↑  |0.5147|±  |0.0050|
+|             |       |none  |     5|acc_norm|↑  |0.7087|±  |0.0045|
+|winogrande   |      1|none  |     5|acc     |↑  |0.6811|±  |0.0131|
 # Uploaded  model