Sentence Similarity
sentence-transformers
Safetensors
English
qwen3
unsloth
feature-extraction
dense
Generated from Trainer
dataset_size:223748
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use Rnfudge/snapd-embedder-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Rnfudge/snapd-embedder-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Rnfudge/snapd-embedder-v1") sentences = [ "What is the significance of the IPv6 multicast address ff02::1?", "Felt board for classroom activities", "In the provided network output, the frequent appearance of `ff020000000000000000000000000001` across various interfaces like `lo`, `eth0`, and `eth1` indicates that these interfaces are correctly configured for basic IPv6 operations. Every active IPv6 interface on a segment must listen for messages sent to `ff02::1` to participate in essential link-local protocols, making its presence a standard and expected entry.", "Not all customizations are supported across all snapd image types or models. For example, certain customizations might be unsupported for UC20+ or classic models, leading to errors. Additionally, if a gadget snap itself defines `defaults` in its `meta/gadget.yaml`, these can be overridden or complemented by the `Customizations` provided during the `SetupSeed` call, affecting system services like SSH." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use Rnfudge/snapd-embedder-v1 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 Rnfudge/snapd-embedder-v1 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 Rnfudge/snapd-embedder-v1 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Rnfudge/snapd-embedder-v1 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Rnfudge/snapd-embedder-v1", max_seq_length=2048, )
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