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
- sentence-transformers
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 new
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)
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