Instructions to use fbaldassarri/HuggingFaceTB_SmolLM2-1.7B-Instruct-auto_gptq-int4-gs128-asym with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use fbaldassarri/HuggingFaceTB_SmolLM2-1.7B-Instruct-auto_gptq-int4-gs128-asym with Transformers:

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

pipe = pipeline("text-generation", model="fbaldassarri/HuggingFaceTB_SmolLM2-1.7B-Instruct-auto_gptq-int4-gs128-asym")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("fbaldassarri/HuggingFaceTB_SmolLM2-1.7B-Instruct-auto_gptq-int4-gs128-asym")
model = AutoModelForMultimodalLM.from_pretrained("fbaldassarri/HuggingFaceTB_SmolLM2-1.7B-Instruct-auto_gptq-int4-gs128-asym")
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]:]))

Transformers.js

How to use fbaldassarri/HuggingFaceTB_SmolLM2-1.7B-Instruct-auto_gptq-int4-gs128-asym with Transformers.js:

// npm i @huggingface/transformers
import { pipeline } from '@huggingface/transformers';

// Allocate pipeline
const pipe = await pipeline('text-generation', 'fbaldassarri/HuggingFaceTB_SmolLM2-1.7B-Instruct-auto_gptq-int4-gs128-asym');

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use fbaldassarri/HuggingFaceTB_SmolLM2-1.7B-Instruct-auto_gptq-int4-gs128-asym with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "fbaldassarri/HuggingFaceTB_SmolLM2-1.7B-Instruct-auto_gptq-int4-gs128-asym"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "fbaldassarri/HuggingFaceTB_SmolLM2-1.7B-Instruct-auto_gptq-int4-gs128-asym",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/fbaldassarri/HuggingFaceTB_SmolLM2-1.7B-Instruct-auto_gptq-int4-gs128-asym

SGLang

How to use fbaldassarri/HuggingFaceTB_SmolLM2-1.7B-Instruct-auto_gptq-int4-gs128-asym 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 "fbaldassarri/HuggingFaceTB_SmolLM2-1.7B-Instruct-auto_gptq-int4-gs128-asym" \
    --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": "fbaldassarri/HuggingFaceTB_SmolLM2-1.7B-Instruct-auto_gptq-int4-gs128-asym",
		"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 "fbaldassarri/HuggingFaceTB_SmolLM2-1.7B-Instruct-auto_gptq-int4-gs128-asym" \
        --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": "fbaldassarri/HuggingFaceTB_SmolLM2-1.7B-Instruct-auto_gptq-int4-gs128-asym",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use fbaldassarri/HuggingFaceTB_SmolLM2-1.7B-Instruct-auto_gptq-int4-gs128-asym with Docker Model Runner:
```
docker model run hf.co/fbaldassarri/HuggingFaceTB_SmolLM2-1.7B-Instruct-auto_gptq-int4-gs128-asym
```

fbaldassarri commited on Jan 4, 2025

Commit

f5578d1

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1 Parent(s): 782df7b

Update README.md

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@@ -1,24 +1,21 @@
 ---
 language:
 - en
-- de
-- fr
-- it
-- pt
-- hi
-- es
-- th
 license: apache-2.0
 library_name: transformers
 tags:
 - autoround
 - intel
 - gptq
 - autogptq
 - woq
-- meta
 - pytorch
 - transformers
 model_name: SmolLM2 1.7B Instruct
 base_model: HuggingFaceTB/SmolLM2-1.7B-Instruct
 inference: false

 ---
 language:
 - en
 license: apache-2.0
 library_name: transformers
 tags:
 - autoround
+- auto-round
 - intel
 - gptq
+- auto-gptq
 - autogptq
 - woq
 - pytorch
 - transformers
+- safetensors
+- onnx
+- transformers.js
 model_name: SmolLM2 1.7B Instruct
 base_model: HuggingFaceTB/SmolLM2-1.7B-Instruct
 inference: false