Instructions to use unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2 with sentence-transformers:

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2")

sentences = [
    "search_query: i love autotrain",
    "search_query: huggingface auto train",
    "search_query: hugging face auto train",
    "search_query: i love autotrain"
]
embeddings = model.encode(sentences)

similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4]

llama-cpp-python

How to use unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2 with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2",
	filename="SmolLM-135M-Instruct-DEVINator-v0.2.gguf",
)

llm.create_chat_completion(
	messages = "{\n    \"source_sentence\": \"That is a happy person\",\n    \"sentences\": [\n        \"That is a happy dog\",\n        \"That is a very happy person\",\n        \"Today is a sunny day\"\n    ]\n}"
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2 with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2
# Run inference directly in the terminal:
llama-cli -hf unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2
# Run inference directly in the terminal:
llama-cli -hf unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2

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 unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2
# Run inference directly in the terminal:
./llama-cli -hf unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2

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 unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2
# Run inference directly in the terminal:
./build/bin/llama-cli -hf unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2

Use Docker

docker model run hf.co/unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2

LM Studio
Jan
Ollama
How to use unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2 with Ollama:
```
ollama run hf.co/unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2
```

Unsloth Studio

How to use unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2 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 unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2 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 unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2 to start chatting

Docker Model Runner
How to use unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2 with Docker Model Runner:
```
docker model run hf.co/unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2
```

Lemonade

How to use unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2

Run and chat with the model

lemonade run user.SmolLM-135M-Instruct-DEVINator-v0.2-{{QUANT_TAG}}

List all available models

lemonade list

AVAILABLE ON OLLAMA: https://ollama.com/unclemusclez/smollm-135m-instruct-devinator

Model Trained Using AutoTrain

Problem type: Sentence Transformers

Validation Metrics

No validation metrics available

Usage

Direct Usage (Sentence Transformers)

First install the Sentence Transformers library:

pip install -U sentence-transformers

Then you can load this model and run inference.

from sentence_transformers import SentenceTransformer

# Download from the Hugging Face Hub
model = SentenceTransformer("sentence_transformers_model_id")
# Run inference
sentences = [
    'search_query: autotrain',
    'search_query: auto train',
    'search_query: i love autotrain',
]
embeddings = model.encode(sentences)
print(embeddings.shape)

# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)