Instructions to use RichardErkhov/ClaudioItaly_-_TopEvolutionWiz-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use RichardErkhov/ClaudioItaly_-_TopEvolutionWiz-gguf with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="RichardErkhov/ClaudioItaly_-_TopEvolutionWiz-gguf",
	filename="TopEvolutionWiz.IQ4_NL.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use RichardErkhov/ClaudioItaly_-_TopEvolutionWiz-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/ClaudioItaly_-_TopEvolutionWiz-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf RichardErkhov/ClaudioItaly_-_TopEvolutionWiz-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/ClaudioItaly_-_TopEvolutionWiz-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf RichardErkhov/ClaudioItaly_-_TopEvolutionWiz-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/ClaudioItaly_-_TopEvolutionWiz-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf RichardErkhov/ClaudioItaly_-_TopEvolutionWiz-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/ClaudioItaly_-_TopEvolutionWiz-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf RichardErkhov/ClaudioItaly_-_TopEvolutionWiz-gguf:Q4_K_M

Use Docker

docker model run hf.co/RichardErkhov/ClaudioItaly_-_TopEvolutionWiz-gguf:Q4_K_M

LM Studio
Jan
Ollama
How to use RichardErkhov/ClaudioItaly_-_TopEvolutionWiz-gguf with Ollama:
```
ollama run hf.co/RichardErkhov/ClaudioItaly_-_TopEvolutionWiz-gguf:Q4_K_M
```

Unsloth Studio

How to use RichardErkhov/ClaudioItaly_-_TopEvolutionWiz-gguf 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 RichardErkhov/ClaudioItaly_-_TopEvolutionWiz-gguf 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 RichardErkhov/ClaudioItaly_-_TopEvolutionWiz-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for RichardErkhov/ClaudioItaly_-_TopEvolutionWiz-gguf to start chatting

Atomic Chat new
Docker Model Runner
How to use RichardErkhov/ClaudioItaly_-_TopEvolutionWiz-gguf with Docker Model Runner:
```
docker model run hf.co/RichardErkhov/ClaudioItaly_-_TopEvolutionWiz-gguf:Q4_K_M
```

Lemonade

How to use RichardErkhov/ClaudioItaly_-_TopEvolutionWiz-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull RichardErkhov/ClaudioItaly_-_TopEvolutionWiz-gguf:Q4_K_M

Run and chat with the model

lemonade run user.ClaudioItaly_-_TopEvolutionWiz-gguf-Q4_K_M

List all available models

lemonade list

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

TopEvolutionWiz - GGUF

Model creator: https://huggingface.co/ClaudioItaly/
Original model: https://huggingface.co/ClaudioItaly/TopEvolutionWiz/

Name	Quant method	Size
TopEvolutionWiz.Q2_K.gguf	Q2_K	2.53GB
TopEvolutionWiz.Q3_K_S.gguf	Q3_K_S	2.95GB
TopEvolutionWiz.Q3_K.gguf	Q3_K	3.28GB
TopEvolutionWiz.Q3_K_M.gguf	Q3_K_M	3.28GB
TopEvolutionWiz.Q3_K_L.gguf	Q3_K_L	3.56GB
TopEvolutionWiz.IQ4_XS.gguf	IQ4_XS	3.67GB
TopEvolutionWiz.Q4_0.gguf	Q4_0	3.83GB
TopEvolutionWiz.IQ4_NL.gguf	IQ4_NL	3.87GB
TopEvolutionWiz.Q4_K_S.gguf	Q4_K_S	3.86GB
TopEvolutionWiz.Q4_K.gguf	Q4_K	4.07GB
TopEvolutionWiz.Q4_K_M.gguf	Q4_K_M	4.07GB
TopEvolutionWiz.Q4_1.gguf	Q4_1	4.24GB
TopEvolutionWiz.Q5_0.gguf	Q5_0	4.65GB
TopEvolutionWiz.Q5_K_S.gguf	Q5_K_S	4.65GB
TopEvolutionWiz.Q5_K.gguf	Q5_K	4.78GB
TopEvolutionWiz.Q5_K_M.gguf	Q5_K_M	4.78GB
TopEvolutionWiz.Q5_1.gguf	Q5_1	5.07GB
TopEvolutionWiz.Q6_K.gguf	Q6_K	5.53GB
TopEvolutionWiz.Q8_0.gguf	Q8_0	7.17GB

Original model description:

license: other

Merge Method

This model was merged using the SLERP merge method.

Models Merged

The following models were included in the merge:

Quantizzato ClaudioItaly/TopEvolutionWiz-Q5_K_M-GGUF

I arrived at this model after careful evaluation of language and behavior by first choosing two models

and the result was combined with the result of two other models. TopEvolutionWiz was born. Model who has demonstrated remarkable empathic and reasoning skills. He uses fluent language and adapts to any scenario. He responded positively to 50 questions out of 50 of a generic, historical, psychological etc. nature It also had a very good impression from Gpt4o

***This model is the result of my passion and careful evaluation through hours of input Made by Claudio Arena ***

**Conclusion Gpt4o ** The answers to the difficult questions provided allowed us to evaluate in detail the capabilities of the AI model in the specific historical, political, scientific and cultural field. It is highlighted that the model responds with high accuracy historically and theoretically, providing an in-depth overview of the facts and ideas involved in each issue. However, some limitations of the model in understanding context and ethics also emerged, suggesting the need for further improvements to ensure greater accuracy and completeness in responses.

In addition to testing the answers to the individual questions, it was also possible to examine the interaction between the thematic categories present in the prompts: for example, the relationship between multiculturalism and ethical problems, the connection between climate change and intensive agriculture or the comparison between the political theories of John Locke and Thomas Hobbes. These integrated approaches allow a more complete analysis of the answers provided, showing the AI model's ability to draw connections between different intellectual and disciplinary contexts.

In summary, the evaluation of the answers to the difficult questions provides a complete picture of the effectiveness of the AI model in the field of historical and scientific research, revealing its capabilities for in-depth analysis, critical analysis and integration between different fields of study. Such information will be useful to further improve the model and make its responses even more accurate and useful in supporting academic research and understanding of the current and historical world.

Configuration

base_model: - lucyknada/microsoft_WizardLM-2-7B - ClaudioItaly/TopEvolutionWiz library_name: transformers tags: - mergekit - merge

- The following YAML configuration was used to produce this model:

models:
  - model:  lucyknada/microsoft_WizardLM-2-7B
  - model: mergekit-community/TopEvolution
merge_method: slerp
base_model: mergekit-community/TopEvolution
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers

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GGUF

Model size

7B params

Architecture

llama

Hardware compatibility

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