Instructions to use RichardErkhov/billy49_-_MiniProject_Submission_1-gguf 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 RichardErkhov/billy49_-_MiniProject_Submission_1-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 RichardErkhov/billy49_-_MiniProject_Submission_1-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf RichardErkhov/billy49_-_MiniProject_Submission_1-gguf:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf RichardErkhov/billy49_-_MiniProject_Submission_1-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf RichardErkhov/billy49_-_MiniProject_Submission_1-gguf:Q4_K_M
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 RichardErkhov/billy49_-_MiniProject_Submission_1-gguf:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf RichardErkhov/billy49_-_MiniProject_Submission_1-gguf:Q4_K_M
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 RichardErkhov/billy49_-_MiniProject_Submission_1-gguf:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf RichardErkhov/billy49_-_MiniProject_Submission_1-gguf:Q4_K_M
Use Docker
docker model run hf.co/RichardErkhov/billy49_-_MiniProject_Submission_1-gguf:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use RichardErkhov/billy49_-_MiniProject_Submission_1-gguf with Ollama:
ollama run hf.co/RichardErkhov/billy49_-_MiniProject_Submission_1-gguf:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use RichardErkhov/billy49_-_MiniProject_Submission_1-gguf with Docker Model Runner:
docker model run hf.co/RichardErkhov/billy49_-_MiniProject_Submission_1-gguf:Q4_K_M
- Lemonade
How to use RichardErkhov/billy49_-_MiniProject_Submission_1-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull RichardErkhov/billy49_-_MiniProject_Submission_1-gguf:Q4_K_M
Run and chat with the model
lemonade run user.billy49_-_MiniProject_Submission_1-gguf-Q4_K_M
List all available models
lemonade list
- Atomic Chat
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Quantization made by Richard Erkhov.
MiniProject_Submission_1 - GGUF
- Model creator: https://huggingface.co/billy49/
- Original model: https://huggingface.co/billy49/MiniProject_Submission_1/
Original model description:
base_model:
- mistralai/Mistral-7B-v0.1
- mistralai/Mistral-7B-Instruct-v0.3 library_name: transformers tags:
- mergekit
- merge
merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the SLERP merge method.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
slices:
- sources:
- model: mistralai/Mistral-7B-v0.1
layer_range:
- 0
- 32
- model: mistralai/Mistral-7B-Instruct-v0.3
layer_range:
- 0
- 32
merge_method: slerp
base_model: mistralai/Mistral-7B-v0.1
parameters:
t:
- filter: self_attn
value:
- 0
- 0.5
- 0.3
- 0.7
- 1
- filter: mlp
value:
- 1
- 0.5
- 0.7
- 0.3
- 0
- value: 0.5
dtype: bfloat16
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