Instructions to use RichardErkhov/Elfrino_-_AndroidPrincess-20B-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use RichardErkhov/Elfrino_-_AndroidPrincess-20B-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/Elfrino_-_AndroidPrincess-20B-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf RichardErkhov/Elfrino_-_AndroidPrincess-20B-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/Elfrino_-_AndroidPrincess-20B-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf RichardErkhov/Elfrino_-_AndroidPrincess-20B-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/Elfrino_-_AndroidPrincess-20B-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf RichardErkhov/Elfrino_-_AndroidPrincess-20B-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/Elfrino_-_AndroidPrincess-20B-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf RichardErkhov/Elfrino_-_AndroidPrincess-20B-gguf:Q4_K_M

Use Docker

docker model run hf.co/RichardErkhov/Elfrino_-_AndroidPrincess-20B-gguf:Q4_K_M

LM Studio
Jan
Ollama
How to use RichardErkhov/Elfrino_-_AndroidPrincess-20B-gguf with Ollama:
```
ollama run hf.co/RichardErkhov/Elfrino_-_AndroidPrincess-20B-gguf:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use RichardErkhov/Elfrino_-_AndroidPrincess-20B-gguf with Docker Model Runner:
```
docker model run hf.co/RichardErkhov/Elfrino_-_AndroidPrincess-20B-gguf:Q4_K_M
```

Lemonade

How to use RichardErkhov/Elfrino_-_AndroidPrincess-20B-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull RichardErkhov/Elfrino_-_AndroidPrincess-20B-gguf:Q4_K_M

Run and chat with the model

lemonade run user.Elfrino_-_AndroidPrincess-20B-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.

Github

Discord

Request more models

AndroidPrincess-20B - GGUF

Model creator: https://huggingface.co/Elfrino/
Original model: https://huggingface.co/Elfrino/AndroidPrincess-20B/

Name	Quant method	Size
AndroidPrincess-20B.Q2_K.gguf	Q2_K	6.91GB
AndroidPrincess-20B.IQ3_XS.gguf	IQ3_XS	7.63GB
AndroidPrincess-20B.IQ3_S.gguf	IQ3_S	8.06GB
AndroidPrincess-20B.Q3_K_S.gguf	Q3_K_S	8.06GB
AndroidPrincess-20B.IQ3_M.gguf	IQ3_M	8.53GB
AndroidPrincess-20B.Q3_K.gguf	Q3_K	9.04GB
AndroidPrincess-20B.Q3_K_M.gguf	Q3_K_M	9.04GB
AndroidPrincess-20B.Q3_K_L.gguf	Q3_K_L	9.9GB
AndroidPrincess-20B.IQ4_XS.gguf	IQ4_XS	10.01GB
AndroidPrincess-20B.Q4_0.gguf	Q4_0	10.52GB
AndroidPrincess-20B.IQ4_NL.gguf	IQ4_NL	10.57GB
AndroidPrincess-20B.Q4_K_S.gguf	Q4_K_S	10.59GB
AndroidPrincess-20B.Q4_K.gguf	Q4_K	11.22GB
AndroidPrincess-20B.Q4_K_M.gguf	Q4_K_M	11.22GB
AndroidPrincess-20B.Q4_1.gguf	Q4_1	11.67GB
AndroidPrincess-20B.Q5_0.gguf	Q5_0	12.83GB
AndroidPrincess-20B.Q5_K_S.gguf	Q5_K_S	12.83GB
AndroidPrincess-20B.Q5_K.gguf	Q5_K	13.18GB
AndroidPrincess-20B.Q5_K_M.gguf	Q5_K_M	13.18GB
AndroidPrincess-20B.Q5_1.gguf	Q5_1	13.98GB
AndroidPrincess-20B.Q6_K.gguf	Q6_K	15.28GB
AndroidPrincess-20B.Q8_0.gguf	Q8_0	19.79GB

Original model description:

base_model:

Elfrino/XwinXtended-20B
seb-c/Psydestroyer-20B library_name: transformers tags:
mergekit
merge

NOTES: LOOKS PROMISING SO FAR..... IN TESTING......*

Some findings: Articulate, long flowy sentences and can be pushed to high temps. Lacks the zany outlandish creativity of PsymedRP-20B or Xwin-MLewd-20B but it's still a solid story weaver..

##################################################################################################################

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:

NEXT TRIAL: make WizardLM into a 20B and SLERP it with XwinXtended? maybe....



slices:
  - sources:
      - model: seb-c/Psydestroyer-20B
        layer_range: [0, 62]
      - model: Elfrino/XwinXtended-20B
        layer_range: [0, 62]
merge_method: slerp
base_model: seb-c/Psydestroyer-20B
parameters:
  t:
    - filter: self_attn
      value: [0.8, 0.8, 0.9, 0.7, .8]
    - filter: mlp
      value: [.8, 0.8, 0.9, 0.8, .7]
    - value: 0.3369
dtype: bfloat16

Downloads last month: 133

GGUF

Model size

20B params

Architecture

llama

Hardware compatibility

2-bit

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8-bit

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