Instructions to use DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix 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 DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix: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 DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix: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 DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix:Q4_K_M

Use Docker

docker model run hf.co/DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix:Q4_K_M

LM Studio
Jan

vLLM

How to use DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix:Q4_K_M

Ollama
How to use DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix with Ollama:
```
ollama run hf.co/DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix:Q4_K_M
```

Unsloth Studio

How to use DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix 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 DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix 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 DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix to start chatting

Docker Model Runner
How to use DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix with Docker Model Runner:
```
docker model run hf.co/DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix:Q4_K_M
```

Lemonade

How to use DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix:Q4_K_M

Run and chat with the model

lemonade run user.Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix-Q4_K_M

List all available models

lemonade list

Atomic Chat

DavidAU commited on May 29, 2024

Commit

dca58b7

verified ·

1 Parent(s): ffb008a

Update README.md

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@@ -17,7 +17,7 @@ tags:
 [uploads in progress]
-<font color=red><h3> Ultra High Remaster of the incredible: Psyonic-Cetacean-20b - Imatrix Plus. </h3></font>
 This is a Floating Point 32 upscale, where all components and merges were remastered to floating point 32.
 This includes all the merges (recreated with master files), and where possible subbing full FP32 models.
@@ -76,6 +76,22 @@ The mountain moved:
 150 points better: PPL = 8.5850 +/- 0.05881  VS: BASE/ORGINAL: PPL = 8.6012 +/- 0.05900
 <B>The bottom line here is this:</b>
 Higher quality instruction following and output.

 [uploads in progress]
+<font color=red><h3> Ultra Quality High Remaster of the incredible: Psyonic-Cetacean-20b - Imatrix Plus. </h3></font>
 This is a Floating Point 32 upscale, where all components and merges were remastered to floating point 32.
 This includes all the merges (recreated with master files), and where possible subbing full FP32 models.
 150 points better: PPL = 8.5850 +/- 0.05881  VS: BASE/ORGINAL: PPL = 8.6012 +/- 0.05900
+<B>THE RESULTS ARE IN: </b>
+AS per Jeb Carter, orginal creator of the model:
+    - instruction following has improved dramatically.
+    - new abilities have emerged.
+    - he had to REDUCE the instructions sets used because the model no longer needed as specific instructions.
+    - prose, nuance and depth have all improved.
+    - known issues with the original model have disappeared.
+This is not "something for nothing" ; it is method of ensuring maximum precision at every step just before "ggufing" the model.
+The methods employed only ensure precision loss is minimized or eliminated.
+It is mathematical and theory sound.
 <B>The bottom line here is this:</b>
 Higher quality instruction following and output.