Feature Extraction
sentence-transformers
ONNX
Safetensors
GGUF
English
code
roberta
python
javascript
go
java
ruby
php
code-search
code-embeddings
multilingual
matryoshka
unixcoder
mteb
Eval Results (legacy)
text-embeddings-inference
Instructions to use divakantpandey/code-embed-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use divakantpandey/code-embed-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("divakantpandey/code-embed-v2") 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] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use divakantpandey/code-embed-v2 with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible embeddings server: llama serve -hf divakantpandey/code-embed-v2:Q8_0 --embeddings
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible embeddings server: llama serve -hf divakantpandey/code-embed-v2:Q8_0 --embeddings
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible embeddings server: ./llama-server -hf divakantpandey/code-embed-v2:Q8_0 --embeddings
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 embeddings server: ./build/bin/llama-server -hf divakantpandey/code-embed-v2:Q8_0 --embeddings
- LM Studio
- Jan
- Ollama
How to use divakantpandey/code-embed-v2 with Ollama:
ollama run hf.co/divakantpandey/code-embed-v2:Q8_0
- Unsloth Desktop
- Docker Model Runner
How to use divakantpandey/code-embed-v2 with Docker Model Runner:
docker model run hf.co/divakantpandey/code-embed-v2:Q8_0
- Lemonade
How to use divakantpandey/code-embed-v2 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull divakantpandey/code-embed-v2:Q8_0
Run and chat with the model
lemonade run user.code-embed-v2-Q8_0
List all available models
lemonade list
- Atomic Chat
Commit History
Today
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Upload README.md with huggingface_hub
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Upload README.md with huggingface_hub
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Upload README.md with huggingface_hub
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Yesterday
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docs: sort model-index and scorecard with lower ranks first (Rank #3 on CoREB, #8 on CoIR, #9 on MTEB Code)
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docs: add top compact rankings (Rank #3 on CoREB, #8 on CoIR, #9 on MTEB Code) and sort lower ranks first
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2 days ago
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docs: update model card with official MTEB leaderboard scores, ranks, and achievements (Oct 23, 2026 snapshot)
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3 days ago
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docs: update context window to 8192 tokens in README
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docs: sync README with production usage examples and verified MTEB rankings
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Update code-embed-v2: Fast Lane fine-tuned weights (+21.52% macro gain across 17 MTEB benchmarks)
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4 days ago
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docs: highlight 8,192 token context window in model card
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clean: remove duplicate folders (sentence_transformers, backbone), remove legacy weights, sync max_seq_length to 1024
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Release CodeEmbed v2: Multilingual code embeddings (MTEB 40.64% NDCG@10)
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