SmolLM 135M Instruct Trained on DEVINator Data for Open Hands (Open Devin)
12 Pulls Updated 8 weeks ago
Readme
https://huggingface.co/unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.1 https://huggingface.co/unclemusclez/SmolLM-135M-Instruct-DEVINator-v0.2
library_name: sentence-transformers tags: - sentence-transformers - sentence-similarity - feature-extraction - autotrain base_model: HuggingFaceTB/SmolLM-135M-Instruct widget: - source_sentence: ‘search_query: i love autotrain’ sentences: - ‘search_query: huggingface auto train’ - ‘search_query: hugging face auto train’ - ‘search_query: i love autotrain’ pipeline_tag: sentence-similarity datasets:
- skratos115/opendevin_DataDevinator
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)