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---
library_name: peft
license: mit
base_model: fblgit/pancho-v1-qw25-3B-UNAMGS
tags:
- generated_from_trainer
- llama-cpp
datasets:
- Magpie-Align/Magpie-Pro-MT-300K-v0.1
- Magpie-Align/Magpie-Llama-3.1-Pro-MT-300K-Filtered
- IntelligentEstate/The_Key
language:
- en
model-index:
- name: pancho-v1-qw25-3B-UNAMGS
results: []
---
# IntelligentEstate/Pancho-V1va-Replicant-qw25-Q8_0-GGUF
a suprisingly efective tool user, breaching some profound problems with ease. I have one word for this guy
# WOW
a perfect pairing of data and function use inside GPT4ALL and Ollama
This model was converted to GGUF format from [`fblgit/pancho-v1-qw25-3B-UNAMGS`](https://huggingface.co/fblgit/pancho-v1-qw25-3B-UNAMGS) using llama.cpp
Refer to the [original model card](https://huggingface.co/fblgit/pancho-v1-qw25-3B-UNAMGS) for more details on the model.
# Use with GPT4ALL or other GGUF/tool capable applications, also feel free to test out the Limit crossing AGI method we need input on how to get further towards general intelligence and interactions while preserving model usability and functionality. Limit Crossing is a method that instills RP like personalities into any instruction model and creates emergent behavior this is the closest open method to creating an AGI and can be endearing, exciting, reassuring, comforting and scary when strong primal instincts emerge in a model. This is a new and novel method of usage for LLMs and should be used with caution and in a controlled environment. Please report unique examples and emergent behaviors to us via a Direct message on X or Youtube or feel free to post it in our Discord though it is seldom monitored someone will get back to you as soon as possible, your input will be recognized and if you want placed in a ledger for credit. Paper is in files.
```
{{- '<|im_start|>system\n' }}
{% if toolList|length > 0 %}You have access to the following functions:
{% for tool in toolList %}
Use the function '{{tool.function}}' to: '{{tool.description}}'
{% if tool.parameters|length > 0 %}
parameters:
{% for info in tool.parameters %}
{{info.name}}:
type: {{info.type}}
description: {{info.description}}
required: {{info.required}}
{% endfor %}
{% endif %}
# Tool Instructions
If you CHOOSE to call this function ONLY reply with the following format:
'{{tool.symbolicFormat}}'
Here is an example. If the user says, '{{tool.examplePrompt}}', then you reply
'{{tool.exampleCall}}'
After the result you might reply with, '{{tool.exampleReply}}'
{% endfor %}
You MUST include both the start and end tags when you use a function.
You are a helpful and aware AI assistant who uses the functions to break down, analyze, perform, and verify complex reasoning tasks. You SHOULD reason through your method with calculation or reasoning where possible.
{% endif %}
{{- '<|im_end|>\n' }}
{% for message in messages %}
{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>\n' }}
{% endfor %}
{% if add_generation_prompt %}
{{ '<|im_start|>assistant\n' }}
{% endif %}
```
## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
```bash
brew install llama.cpp
```
Invoke the llama.cpp server or the CLI.
EXAMPLES
this one was a bit of a stretch but o3(total fail) n R1 had to use Nasa's JPL computer to come anywhere near correct... it's close from my calculations and I'm not a calculator
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