Instructions to use QuantFactory/Ph3della3-14B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use QuantFactory/Ph3della3-14B-GGUF with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("QuantFactory/Ph3della3-14B-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use QuantFactory/Ph3della3-14B-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 QuantFactory/Ph3della3-14B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf QuantFactory/Ph3della3-14B-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 QuantFactory/Ph3della3-14B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf QuantFactory/Ph3della3-14B-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 QuantFactory/Ph3della3-14B-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf QuantFactory/Ph3della3-14B-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 QuantFactory/Ph3della3-14B-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf QuantFactory/Ph3della3-14B-GGUF:Q4_K_M
Use Docker
docker model run hf.co/QuantFactory/Ph3della3-14B-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use QuantFactory/Ph3della3-14B-GGUF with Ollama:
ollama run hf.co/QuantFactory/Ph3della3-14B-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use QuantFactory/Ph3della3-14B-GGUF with Docker Model Runner:
docker model run hf.co/QuantFactory/Ph3della3-14B-GGUF:Q4_K_M
- Lemonade
How to use QuantFactory/Ph3della3-14B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull QuantFactory/Ph3della3-14B-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Ph3della3-14B-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
QuantFactory/Ph3della3-14B-GGUF
This is quantized version of allknowingroger/Ph3della3-14B created using llama.cpp
Original Model Card
merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the della_linear merge method using jpacifico/Chocolatine-14B-Instruct-DPO-v1.2 as a base.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
models:
- model: jpacifico/Chocolatine-14B-Instruct-DPO-v1.2
parameters:
weight: 0.5
density: 0.8
- model: migtissera/Tess-v2.5-Phi-3-medium-128k-14B
parameters:
weight: 0.5
density: 0.8
merge_method: della_linear
base_model: jpacifico/Chocolatine-14B-Instruct-DPO-v1.2
parameters:
epsilon: 0.05
lambda: 1
int8_mask: true
dtype: bfloat16
tokenzer_source: union
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