How to use second-state/E5-Mistral-7B-Instruct-Embedding-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="second-state/E5-Mistral-7B-Instruct-Embedding-GGUF")
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("second-state/E5-Mistral-7B-Instruct-Embedding-GGUF") model = AutoModel.from_pretrained("second-state/E5-Mistral-7B-Instruct-Embedding-GGUF", device_map="auto")
How to use second-state/E5-Mistral-7B-Instruct-Embedding-GGUF with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible embeddings server: llama serve -hf second-state/E5-Mistral-7B-Instruct-Embedding-GGUF:Q4_K_M --embeddings
winget install llama.cpp # Start a local OpenAI-compatible embeddings server: llama serve -hf second-state/E5-Mistral-7B-Instruct-Embedding-GGUF:Q4_K_M --embeddings
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible embeddings server: ./build/bin/llama serve -hf second-state/E5-Mistral-7B-Instruct-Embedding-GGUF:Q4_K_M --embeddings
How to use second-state/E5-Mistral-7B-Instruct-Embedding-GGUF with Ollama:
ollama run hf.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF:Q4_K_M
How to use second-state/E5-Mistral-7B-Instruct-Embedding-GGUF with Docker Model Runner:
docker model run hf.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF:Q4_K_M
How to use second-state/E5-Mistral-7B-Instruct-Embedding-GGUF with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull second-state/E5-Mistral-7B-Instruct-Embedding-GGUF:Q4_K_M
lemonade run user.E5-Mistral-7B-Instruct-Embedding-GGUF-Q4_K_M
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