Feature Extraction
Safetensors
GGUF
English
llama.cpp
embeddings
sentence-similarity
retrieval
medical
biomedical
bitnet
1.58-bit
ternary
llm2vec
Instructions to use Rabe3/1-bit-embedding-general with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Rabe3/1-bit-embedding-general with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Rabe3/1-bit-embedding-general", filename="medbit-2b-embed.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Rabe3/1-bit-embedding-general 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 Rabe3/1-bit-embedding-general # Run inference directly in the terminal: llama cli -hf Rabe3/1-bit-embedding-general
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Rabe3/1-bit-embedding-general # Run inference directly in the terminal: llama cli -hf Rabe3/1-bit-embedding-general
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf Rabe3/1-bit-embedding-general # Run inference directly in the terminal: ./llama-cli -hf Rabe3/1-bit-embedding-general
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 server with a web UI: ./build/bin/llama-server -hf Rabe3/1-bit-embedding-general # Run inference directly in the terminal: ./build/bin/llama-cli -hf Rabe3/1-bit-embedding-general
Use Docker
docker model run hf.co/Rabe3/1-bit-embedding-general
- LM Studio
- Jan
- Ollama
How to use Rabe3/1-bit-embedding-general with Ollama:
ollama run hf.co/Rabe3/1-bit-embedding-general
- Unsloth Studio
How to use Rabe3/1-bit-embedding-general 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 Rabe3/1-bit-embedding-general 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 Rabe3/1-bit-embedding-general to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Rabe3/1-bit-embedding-general to start chatting
- Atomic Chat new
- Docker Model Runner
How to use Rabe3/1-bit-embedding-general with Docker Model Runner:
docker model run hf.co/Rabe3/1-bit-embedding-general
- Lemonade
How to use Rabe3/1-bit-embedding-general with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Rabe3/1-bit-embedding-general
Run and chat with the model
lemonade run user.1-bit-embedding-general-{{QUANT_TAG}}List all available models
lemonade list
| { | |
| "architectures": [ | |
| "BitNetModel" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "auto_map": { | |
| "AutoConfig": "configuration_bitnet.BitNetConfig", | |
| "AutoModelForCausalLM": "modeling_bitnet.BitNetForCausalLM" | |
| }, | |
| "bos_token_id": 128000, | |
| "eos_token_id": 128001, | |
| "hidden_act": "relu2", | |
| "hidden_size": 2560, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 6912, | |
| "max_position_embeddings": 4096, | |
| "model_type": "bitnet", | |
| "num_attention_heads": 20, | |
| "num_hidden_layers": 30, | |
| "num_key_value_heads": 5, | |
| "quantization_config": { | |
| "linear_class": "autobitlinear", | |
| "modules_to_not_convert": null, | |
| "quant_method": "bitnet", | |
| "quantization_mode": "online", | |
| "rms_norm_eps": 1e-06, | |
| "use_rms_norm": false | |
| }, | |
| "rms_norm_eps": 1e-05, | |
| "rope_theta": 500000.0, | |
| "tie_word_embeddings": true, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.53.3", | |
| "use_cache": true, | |
| "vocab_size": 128257 | |
| } | |