Feature Extraction
sentence-transformers
Safetensors
Transformers
qwen3
mteb
text-embeddings-inference
Instructions to use microsoft/harrier-oss-v1-0.6b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use microsoft/harrier-oss-v1-0.6b with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("microsoft/harrier-oss-v1-0.6b") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use microsoft/harrier-oss-v1-0.6b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="microsoft/harrier-oss-v1-0.6b")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("microsoft/harrier-oss-v1-0.6b") model = AutoModel.from_pretrained("microsoft/harrier-oss-v1-0.6b", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Training/finetunning
#2
by AliKhajegiliM - opened
Hello,
Thank you for sharing this model!
I am wondering if any official code for training/fine-tuning of this model will be released?
Hi, if you're on a Mac with Apple Silicon, you can use mlx-tune
In the latest release (v0.4.15), the Harrier-oss-v1 fine-tuning support has been added, checkout here: https://github.com/ARahim3/mlx-tune/releases/tag/v0.4.15