Text Generation
Safetensors
GGUF
English
embeddings-are-overpriced
frozen-embedding
binary-codes
ternary
bitnet
gemma-3
small-language-model
cpu-inference
research
Instructions to use QLNI/embeddings-are-overpriced with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use QLNI/embeddings-are-overpriced with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf QLNI/embeddings-are-overpriced:Q4_K_M # Run inference directly in the terminal: llama cli -hf QLNI/embeddings-are-overpriced:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf QLNI/embeddings-are-overpriced:Q4_K_M # Run inference directly in the terminal: llama cli -hf QLNI/embeddings-are-overpriced:Q4_K_M
Build from source code
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 server with a web UI: ./build/bin/llama serve -hf QLNI/embeddings-are-overpriced:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf QLNI/embeddings-are-overpriced:Q4_K_M
Use Docker
docker model run hf.co/QLNI/embeddings-are-overpriced:Q4_K_M
- Llama new
- LM Studio
- Jan
- vLLM
How to use QLNI/embeddings-are-overpriced with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "QLNI/embeddings-are-overpriced" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "QLNI/embeddings-are-overpriced", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/QLNI/embeddings-are-overpriced:Q4_K_M
- Ollama
How to use QLNI/embeddings-are-overpriced with Ollama:
ollama run hf.co/QLNI/embeddings-are-overpriced:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use QLNI/embeddings-are-overpriced with Docker Model Runner:
docker model run hf.co/QLNI/embeddings-are-overpriced:Q4_K_M
- Lemonade
How to use QLNI/embeddings-are-overpriced with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull QLNI/embeddings-are-overpriced:Q4_K_M
Run and chat with the model
lemonade run user.embeddings-are-overpriced-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download eval/eval_armB_step2.json from QLNI/embeddings-are-overpriced: direct link, hf CLI and curl.
- Browser
- Download file 5.8 kB
-
https://huggingface.co/QLNI/embeddings-are-overpriced/resolve/main/eval/eval_armB_step2.json
- Command line
-
hf download hf://QLNI/embeddings-are-overpriced/eval/eval_armB_step2.json
-
curl -L -o eval_armB_step2.json https://huggingface.co/QLNI/embeddings-are-overpriced/resolve/main/eval/eval_armB_step2.json
5.8 kB
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