Transformers
GGUF
English
HelpingAI
coder
lite
Fine-tuned
Mixture of Experts
nlp
TensorBlock
GGUF
conversational
Instructions to use tensorblock/HelpingAI-Lite-2x1B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tensorblock/HelpingAI-Lite-2x1B-GGUF with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tensorblock/HelpingAI-Lite-2x1B-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use tensorblock/HelpingAI-Lite-2x1B-GGUF 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 tensorblock/HelpingAI-Lite-2x1B-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/HelpingAI-Lite-2x1B-GGUF:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tensorblock/HelpingAI-Lite-2x1B-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/HelpingAI-Lite-2x1B-GGUF:Q2_K
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 tensorblock/HelpingAI-Lite-2x1B-GGUF:Q2_K # Run inference directly in the terminal: ./build/bin/llama cli -hf tensorblock/HelpingAI-Lite-2x1B-GGUF:Q2_K
Use Docker
docker model run hf.co/tensorblock/HelpingAI-Lite-2x1B-GGUF:Q2_K
- Llama new
- LM Studio
- Jan
- Ollama
How to use tensorblock/HelpingAI-Lite-2x1B-GGUF with Ollama:
ollama run hf.co/tensorblock/HelpingAI-Lite-2x1B-GGUF:Q2_K
- Unsloth Desktop
- Docker Model Runner
How to use tensorblock/HelpingAI-Lite-2x1B-GGUF with Docker Model Runner:
docker model run hf.co/tensorblock/HelpingAI-Lite-2x1B-GGUF:Q2_K
- Lemonade
How to use tensorblock/HelpingAI-Lite-2x1B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tensorblock/HelpingAI-Lite-2x1B-GGUF:Q2_K
Run and chat with the model
lemonade run user.HelpingAI-Lite-2x1B-GGUF-Q2_K
List all available models
lemonade list
- Atomic Chat
Download HelpingAI-Lite-2x1B-Q3_K_M.gguf from tensorblock/HelpingAI-Lite-2x1B-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 911 MB
-
https://huggingface.co/tensorblock/HelpingAI-Lite-2x1B-GGUF/resolve/main/HelpingAI-Lite-2x1B-Q3_K_M.gguf
- Command line
-
hf download hf://tensorblock/HelpingAI-Lite-2x1B-GGUF/HelpingAI-Lite-2x1B-Q3_K_M.gguf
-
curl -L -o HelpingAI-Lite-2x1B-Q3_K_M.gguf https://huggingface.co/tensorblock/HelpingAI-Lite-2x1B-GGUF/resolve/main/HelpingAI-Lite-2x1B-Q3_K_M.gguf
911 MB
- Xet hash:
- 0aeb6ad485df9498518f540e682c965501661e3d8ab83d12398958a3a7db639d
- Size of remote file:
- 911 MB
- SHA256:
- 44495100e315a49e90cba3445059d1c67bf283ee85d70f7a241462c247a76eba
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