Instructions to use WhirlwindAI/Arithmetic-SLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use WhirlwindAI/Arithmetic-SLM with Transformers:

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

pipe = pipeline("text-generation", model="WhirlwindAI/Arithmetic-SLM", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("WhirlwindAI/Arithmetic-SLM", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use WhirlwindAI/Arithmetic-SLM with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "WhirlwindAI/Arithmetic-SLM"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "WhirlwindAI/Arithmetic-SLM",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/WhirlwindAI/Arithmetic-SLM

SGLang

How to use WhirlwindAI/Arithmetic-SLM 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 "WhirlwindAI/Arithmetic-SLM" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "WhirlwindAI/Arithmetic-SLM",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "WhirlwindAI/Arithmetic-SLM" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "WhirlwindAI/Arithmetic-SLM",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use WhirlwindAI/Arithmetic-SLM with Docker Model Runner:
```
docker model run hf.co/WhirlwindAI/Arithmetic-SLM
```

PhysiQuanty commited on 9 days ago

Commit

e628e7a

verified ·

1 Parent(s): ea7fa68

Update README.md

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README.md +24 -22

README.md CHANGED Viewed

@@ -1,32 +1,34 @@
 ---
 license: apache-2.0
 language:
-  - en
 tags:
-  - slm
-  - arithmetic
-  - math
-  - causal-lm
-  - text-generation
-  - custom_code
-  - safetensors
 library_name: transformers
 pipeline_tag: text-generation
 metrics:
-  - accuracy
 model-index:
-  - name: Arithmetic-SLM
-    results:
-      - task:
-          type: text-generation
-          name: Arithmetic continuation
-        dataset:
-          type: AxiomicLabs/ArithMark-2.0
-          name: ArithMark-2
-        metrics:
-          - type: accuracy
-            name: Overall
-            value: 78.60
 ---
@@ -282,4 +284,4 @@ This project does not claim to be a revolution.
 It is an experiment in making small models learn precise arithmetic, numerical structure, and eventually parts of their own learning dynamics.
-**By Science AND FOR SCIENCE <3**

 ---
 license: apache-2.0
 language:
+- en
 tags:
+- slm
+- arithmetic
+- math
+- causal-lm
+- text-generation
+- custom_code
+- safetensors
 library_name: transformers
 pipeline_tag: text-generation
 metrics:
+- accuracy
 model-index:
+- name: Arithmetic-SLM
+  results:
+  - task:
+      type: text-generation
+      name: Arithmetic continuation
+    dataset:
+      type: AxiomicLabs/ArithMark-2.0
+      name: ArithMark-2
+    metrics:
+    - type: accuracy
+      name: Overall
+      value: 78.6
+datasets:
+- WhirlwindAI/Arithmetic
 ---
 It is an experiment in making small models learn precise arithmetic, numerical structure, and eventually parts of their own learning dynamics.
+**By Science AND FOR SCIENCE <3**