Instructions to use brittlewis12/Memphis-CoT-3B-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 brittlewis12/Memphis-CoT-3B-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 brittlewis12/Memphis-CoT-3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf brittlewis12/Memphis-CoT-3B-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 brittlewis12/Memphis-CoT-3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf brittlewis12/Memphis-CoT-3B-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 brittlewis12/Memphis-CoT-3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf brittlewis12/Memphis-CoT-3B-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 brittlewis12/Memphis-CoT-3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf brittlewis12/Memphis-CoT-3B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/brittlewis12/Memphis-CoT-3B-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use brittlewis12/Memphis-CoT-3B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "brittlewis12/Memphis-CoT-3B-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "brittlewis12/Memphis-CoT-3B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/brittlewis12/Memphis-CoT-3B-GGUF:Q4_K_M

Ollama
How to use brittlewis12/Memphis-CoT-3B-GGUF with Ollama:
```
ollama run hf.co/brittlewis12/Memphis-CoT-3B-GGUF:Q4_K_M
```

Unsloth Studio

How to use brittlewis12/Memphis-CoT-3B-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 brittlewis12/Memphis-CoT-3B-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 brittlewis12/Memphis-CoT-3B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for brittlewis12/Memphis-CoT-3B-GGUF to start chatting

Docker Model Runner
How to use brittlewis12/Memphis-CoT-3B-GGUF with Docker Model Runner:
```
docker model run hf.co/brittlewis12/Memphis-CoT-3B-GGUF:Q4_K_M
```

Lemonade

How to use brittlewis12/Memphis-CoT-3B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull brittlewis12/Memphis-CoT-3B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Memphis-CoT-3B-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

Memphis-CoT-3B GGUF

Original model: Memphis-CoT-3B Model creator: euclaise

This repo contains GGUF format model files for euclaise’s Memphis-CoT-3B, updated for the latest training run as of 2/2/24.

Memphis-CoT is a finetune of StableLM 3b 4e1t on TinyCoT, along with reddit-instruct (subset to 5000 examples, excluding posts with brackets in the title) and a curated subset of oasst2.

What is GGUF?

GGUF is a file format for representing AI models. It is the third version of the format, introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp. Converted using llama.cpp b2022 (8f8ddfc)

Prompt template:

{{system_message}}
### User:
{{prompt}}
### Assistant:

or Tiny CoT:

### User:
{{prompt}}
### Rationale:
[...]
### Answer:

Download & run with cnvrs on iPhone, iPad, and Mac!

cnvrs is the best app for private, local AI on your device:

create & save Characters with custom system prompts & temperature settings
download and experiment with any GGUF model you can find on HuggingFace!
make it your own with custom Theme colors
powered by Metal ⚡️ & Llama.cpp, with haptics during response streaming!
try it out yourself today, on Testflight!
follow cnvrs on twitter to stay up to date

Original Model Evaluations:

Model	Size	Data	Method	GSM8K (5-shot)	AGIEval (English/Nous subset, acc_norm)	BIG Bench Hard (CoT, few-shot*)
StableLM 3B Base	3B	Base	Base	2.05%	25.14%	36.75%
StableHermes 3B	3B	GPT	SFT	3.64%	24.31%	37.28%
MPT 7B Instruct	7B	Human+Anthropic	SFT	2.05%	24.12%	11.01%
OpenLLaMA 7B v2 open-instruct	7B	Human (nearly: ecqa is an exception)	SFT	8.64%	23.21%	29.84%
StableLM Zephyr 3B	3B	GPT	DPO	possibly contaminated (45.72%)	33.31%	0.91%
Memphis-CoT 3B	3B	Human	Self-teaching	13.8%	26.24%	38.24%

*5-shot, as performed automatically by LM Evaluation Harness bbh_cot_fewshot even with num_fewshot=0

Memphis outperforms other primarily-human-data models that are over twice its size, along with SFT models of its size, and trades with the Zephyr DPO model. That said, Zephyr uses synthetic data, and much more of it.

Downloads last month: 70

GGUF

Model size

3B params

Architecture

stablelm

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

View +1 variant

Model tree for brittlewis12/Memphis-CoT-3B-GGUF

Base model

stabilityai/stablelm-3b-4e1t

Finetuned

euclaise/Memphis-CoT-3B

Quantized

(3)

this model

brittlewis12
/

Memphis-CoT-3B-GGUF