Instructions to use rozek/42dot_LLM-SFT-1.3B_GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use rozek/42dot_LLM-SFT-1.3B_GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="rozek/42dot_LLM-SFT-1.3B_GGUF",
	filename="42dot_LLM-SFT-1.3B.gguf",
)

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

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use rozek/42dot_LLM-SFT-1.3B_GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf rozek/42dot_LLM-SFT-1.3B_GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf rozek/42dot_LLM-SFT-1.3B_GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf rozek/42dot_LLM-SFT-1.3B_GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf rozek/42dot_LLM-SFT-1.3B_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 rozek/42dot_LLM-SFT-1.3B_GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf rozek/42dot_LLM-SFT-1.3B_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 rozek/42dot_LLM-SFT-1.3B_GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf rozek/42dot_LLM-SFT-1.3B_GGUF:Q4_K_M

Use Docker

docker model run hf.co/rozek/42dot_LLM-SFT-1.3B_GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use rozek/42dot_LLM-SFT-1.3B_GGUF with Ollama:
```
ollama run hf.co/rozek/42dot_LLM-SFT-1.3B_GGUF:Q4_K_M
```

Unsloth Studio new

How to use rozek/42dot_LLM-SFT-1.3B_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 rozek/42dot_LLM-SFT-1.3B_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 rozek/42dot_LLM-SFT-1.3B_GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for rozek/42dot_LLM-SFT-1.3B_GGUF to start chatting

Docker Model Runner
How to use rozek/42dot_LLM-SFT-1.3B_GGUF with Docker Model Runner:
```
docker model run hf.co/rozek/42dot_LLM-SFT-1.3B_GGUF:Q4_K_M
```

Lemonade

How to use rozek/42dot_LLM-SFT-1.3B_GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull rozek/42dot_LLM-SFT-1.3B_GGUF:Q4_K_M

Run and chat with the model

lemonade run user.42dot_LLM-SFT-1.3B_GGUF-Q4_K_M

List all available models

lemonade list

42dot_LLM-SFT-1.3B_GGUF

Model Creator: 42dot
original Model: 42dot_LLM-SFT-1.3B

Description

This repository contains the GGUF conversion and the most relevant quantizations of 42dot's 42dot_LLM-SFT-1.3B model - ready to be used with llama.cpp and similar applications.

Files

In order to allow for fine-tuning (the model has the required LLaMA architecture) the original GGUF conversion has been made available

42dot_LLM-SFT-1.3B.gguf

From this file, the following quantizations were derived:

(tell me if you need more)

Usage Details

Any technical details can be found on the original model card The most important ones for using this model are

context length is 4096
there does not seem to be a specific prompt structure - just provide the text you want to be completed

Text Completion with LLaMA.cpp

For simple inferencing, use a command similar to

./main -m 42dot_LLM-SFT-1.3B-Q8_K.gguf --temp 0 --top-k 4 --prompt "who was Joseph Weizenbaum?"

Text Tokenization with LLaMA.cpp

To get a list of tokens, use a command similar to

./tokenization -m 42dot_LLM-SFT-1.3B-Q8_K.gguf --prompt "who was Joseph Weizenbaum?"

Embeddings Calculation with LLaMA.cpp

Text embeddings are calculated with a command similar to

./embedding -m 42dot_LLM-SFT-1.3B-Q8_K.gguf --prompt "who was Joseph Weizenbaum?"

License

The original model "is licensed under the Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC 4.0)" - for that reason, the same license was also chosen for the conversions found in this repository.

So, in order to be fair and give credits to whom they belong:

the original model was created and published by 42dot
besides quantization, no changes were applied to the model itself

Downloads last month: 69

GGUF

Model size

1B params

Architecture

llama

Hardware compatibility

4-bit

5-bit

6-bit

8-bit

View +1 variant

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