Instructions to use jncraton/SmolLM-135M-Instruct-Add with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use jncraton/SmolLM-135M-Instruct-Add with Transformers:

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

pipe = pipeline("text-generation", model="jncraton/SmolLM-135M-Instruct-Add")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("jncraton/SmolLM-135M-Instruct-Add")
model = AutoModelForCausalLM.from_pretrained("jncraton/SmolLM-135M-Instruct-Add")
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 jncraton/SmolLM-135M-Instruct-Add with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "jncraton/SmolLM-135M-Instruct-Add"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "jncraton/SmolLM-135M-Instruct-Add",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/jncraton/SmolLM-135M-Instruct-Add

SGLang

How to use jncraton/SmolLM-135M-Instruct-Add 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 "jncraton/SmolLM-135M-Instruct-Add" \
    --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": "jncraton/SmolLM-135M-Instruct-Add",
		"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 "jncraton/SmolLM-135M-Instruct-Add" \
        --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": "jncraton/SmolLM-135M-Instruct-Add",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use jncraton/SmolLM-135M-Instruct-Add with Docker Model Runner:
```
docker model run hf.co/jncraton/SmolLM-135M-Instruct-Add
```

jncraton commited on Sep 4, 2024

Commit

d90bd87

verified ·

1 Parent(s): ae198e4

Training in progress, step 4

Browse files

Files changed (3) hide show

model.safetensors +1 -1
runs/Sep04_20-10-45_345bdf848cbc/events.out.tfevents.1725480646.345bdf848cbc.10920.1 +3 -0
training_args.bin +1 -1

model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e54b4a015577758570c85a162700367a2e2003412170d8d851bdc94a60940641
 size 538090408

 version https://git-lfs.github.com/spec/v1
+oid sha256:2d2f3e09a14c05931c3819ad599a36bc12149c3edac9ab7ca639a1f1cf554eb5
 size 538090408

runs/Sep04_20-10-45_345bdf848cbc/events.out.tfevents.1725480646.345bdf848cbc.10920.1 ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:b60cb4e2e409c6df7f67cf2326a1a298eb9ca4dfc98c941e91c49df1cedc6f0a
+size 6526

training_args.bin CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9dbf6736c575b0693136cd61c76dcc4af2f92056ba6d8805a70a24a899de62a8
 size 5496

 version https://git-lfs.github.com/spec/v1
+oid sha256:f038cc9930f3ab0c619256f4a603efed7d1c2f976158b0ccfc6c25cae69118a4
 size 5496