Instructions to use Chat-Error/HH2-temp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Chat-Error/HH2-temp with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Chat-Error/HH2-temp", filename="Merged_Q5KM.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use Chat-Error/HH2-temp with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Chat-Error/HH2-temp # Run inference directly in the terminal: llama-cli -hf Chat-Error/HH2-temp
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Chat-Error/HH2-temp # Run inference directly in the terminal: llama-cli -hf Chat-Error/HH2-temp
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 Chat-Error/HH2-temp # Run inference directly in the terminal: ./llama-cli -hf Chat-Error/HH2-temp
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 Chat-Error/HH2-temp # Run inference directly in the terminal: ./build/bin/llama-cli -hf Chat-Error/HH2-temp
Use Docker
docker model run hf.co/Chat-Error/HH2-temp
- LM Studio
- Jan
- Ollama
How to use Chat-Error/HH2-temp with Ollama:
ollama run hf.co/Chat-Error/HH2-temp
- Unsloth Studio new
How to use Chat-Error/HH2-temp 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 Chat-Error/HH2-temp 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 Chat-Error/HH2-temp to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Chat-Error/HH2-temp to start chatting
- Docker Model Runner
How to use Chat-Error/HH2-temp with Docker Model Runner:
docker model run hf.co/Chat-Error/HH2-temp
- Lemonade
How to use Chat-Error/HH2-temp with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Chat-Error/HH2-temp
Run and chat with the model
lemonade run user.HH2-temp-{{QUANT_TAG}}List all available models
lemonade list
metadata
library_name: peft
Training procedure
The following bitsandbytes quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: bfloat16
Framework versions
- PEFT 0.6.0.dev0