Instructions to use Nexuss0781/SmolLM2-135M-Instruct-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use Nexuss0781/SmolLM2-135M-Instruct-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Nexuss0781/SmolLM2-135M-Instruct-GGUF:Q6_K
# Run inference directly in the terminal:
llama cli -hf Nexuss0781/SmolLM2-135M-Instruct-GGUF:Q6_K

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Nexuss0781/SmolLM2-135M-Instruct-GGUF:Q6_K
# Run inference directly in the terminal:
llama cli -hf Nexuss0781/SmolLM2-135M-Instruct-GGUF:Q6_K

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf Nexuss0781/SmolLM2-135M-Instruct-GGUF:Q6_K
# Run inference directly in the terminal:
./llama-cli -hf Nexuss0781/SmolLM2-135M-Instruct-GGUF:Q6_K

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf Nexuss0781/SmolLM2-135M-Instruct-GGUF:Q6_K
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Nexuss0781/SmolLM2-135M-Instruct-GGUF:Q6_K

Use Docker

docker model run hf.co/Nexuss0781/SmolLM2-135M-Instruct-GGUF:Q6_K

LM Studio
Jan

vLLM

How to use Nexuss0781/SmolLM2-135M-Instruct-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Nexuss0781/SmolLM2-135M-Instruct-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Nexuss0781/SmolLM2-135M-Instruct-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Nexuss0781/SmolLM2-135M-Instruct-GGUF:Q6_K

Ollama
How to use Nexuss0781/SmolLM2-135M-Instruct-GGUF with Ollama:
```
ollama run hf.co/Nexuss0781/SmolLM2-135M-Instruct-GGUF:Q6_K
```
Unsloth Desktop
Docker Model Runner
How to use Nexuss0781/SmolLM2-135M-Instruct-GGUF with Docker Model Runner:
```
docker model run hf.co/Nexuss0781/SmolLM2-135M-Instruct-GGUF:Q6_K
```

Lemonade

How to use Nexuss0781/SmolLM2-135M-Instruct-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Nexuss0781/SmolLM2-135M-Instruct-GGUF:Q6_K

Run and chat with the model

lemonade run user.SmolLM2-135M-Instruct-GGUF-Q6_K

List all available models

lemonade list

Atomic Chat

Nexuss0781 commited on Aug 21

Commit

01406a9

verified ·

1 Parent(s): 99eca31

Clarify HuggingFaceTB source ownership and upstream licensing

Browse files

Files changed (1) hide show

README.md +6 -4

README.md CHANGED Viewed

@@ -13,9 +13,11 @@ tags:
 base_model: HuggingFaceTB/SmolLM2-135M-Instruct
 ---
-# SmolLM2 135M Instruct — GGUF
-This repository provides local CPU-oriented GGUF conversions of [`HuggingFaceTB/SmolLM2-135M-Instruct`](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct) for use with `llama.cpp` and compatible runtimes. The original instruct model is a compact 135M-parameter model released under the Apache-2.0 license.
 ## Available files
@@ -58,6 +60,6 @@ sha256sum -c CHECKSUMS.sha256
 The model was converted from the official Hugging Face checkpoint with the official `llama.cpp` Hugging Face-to-GGUF converter. The F16 GGUF output was retained as the quality-preserving variant, then quantized with `llama-quantize` to produce the Q6_K variant. See `conversion-metadata.json` for the artifact metadata.
-## License and attribution
-These GGUF artifacts are derived from [HuggingFaceTB/SmolLM2-135M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct). The upstream model card identifies the model license as **Apache-2.0**. Retain upstream attribution and consult the original model card for limitations, training details, and citation information.

 base_model: HuggingFaceTB/SmolLM2-135M-Instruct
 ---
+# SmolLM2 135M Instruct — Unofficial GGUF Conversions
+> **Original source model and publisher:** [HuggingFaceTB/SmolLM2-135M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct) by **HuggingFaceTB**. This repository contains file-format conversions only. It does **not** claim authorship, ownership, training, or creation of the underlying SmolLM2 model.
+This repository provides local CPU-oriented GGUF conversions of the upstream SmolLM2 135M Instruct model for use with `llama.cpp` and compatible runtimes. The source model's Apache-2.0 license is retained; no separate or replacement license is asserted for the underlying model.
 ## Available files
 The model was converted from the official Hugging Face checkpoint with the official `llama.cpp` Hugging Face-to-GGUF converter. The F16 GGUF output was retained as the quality-preserving variant, then quantized with `llama-quantize` to produce the Q6_K variant. See `conversion-metadata.json` for the artifact metadata.
+## Upstream source, ownership, and license
+The underlying model is published by **HuggingFaceTB** at [HuggingFaceTB/SmolLM2-135M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct). The upstream model card identifies its license as **Apache-2.0**. The conversion distributor claims no ownership or authorship of the original model and does not impose a new license on it. Retain the upstream attribution and consult the source model card for limitations, training details, and citation information.