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---
license: cc-by-sa-4.0
---
# StableLM-3B-4E1T #
* Model Creator: [Stability AI](https://huggingface.co/stabilityai)
* original Model: [StableLM-3B-4E1T](https://huggingface.co/stabilityai/stablelm-3b-4e1t)
## Description ##
This repository contains the most relevant quantizations of Stability AI's
[StableLM-3B-4E1T](https://huggingface.co/stabilityai/stablelm-3b-4e1t) model
in GGUF format - ready to be used with
[llama.cpp](https://github.com/ggerganov/llama.cpp) and similar applications.
## About StableLM-3B-4E1T ##
Stability AI claims: "_StableLM-3B-4E1T achieves
state-of-the-art performance (September 2023) at the 3B parameter scale
for open-source models and is competitive with many of the popular
contemporary 7B models, even outperforming our most recent 7B
StableLM-Base-Alpha-v2._"
According to them "_The model is intended to be used as a foundational base
model for application-specific fine-tuning. Developers must evaluate and
fine-tune the model for safe performance in downstream applications._"
## Files ##
Right now, the following quantizations are available:
* [stablelm-3b-4e1t-Q3_K_M](https://huggingface.co/rozek/StableLM-3B-4E1T_GGUF/blob/main/stablelm-3b-4e1t-Q3_K_M.bin)
* [stablelm-3b-4e1t-Q4_K_M](https://huggingface.co/rozek/StableLM-3B-4E1T_GGUF/blob/main/stablelm-3b-4e1t-Q4_K_M.bin)
* [stablelm-3b-4e1t-Q5_K_M](https://huggingface.co/rozek/StableLM-3B-4E1T_GGUF/blob/main/stablelm-3b-4e1t-Q5_K_M.bin)
* [stablelm-3b-4e1t-Q6_K](https://huggingface.co/rozek/StableLM-3B-4E1T_GGUF/blob/main/stablelm-3b-4e1t-Q6_K.bin)
* [stablelm-3b-4e1t-Q8_K](https://huggingface.co/rozek/StableLM-3B-4E1T_GGUF/blob/main/stablelm-3b-4e1t-Q8_K.bin)
(tell me if you need more)
These files are presented here with the written permission of Stability AI (although
access to the model itself is still "gated").
## Usage Details ##
Any technical details can be found on the
[original model card](https://huggingface.co/stabilityai/stablelm-3b-4e1t) and in
a paper on [StableLM-3B-4E1T](https://stability.wandb.io/stability-llm/stable-lm/reports/StableLM-3B-4E1T--VmlldzoyMjU4?accessToken=u3zujipenkx5g7rtcj9qojjgxpconyjktjkli2po09nffrffdhhchq045vp0wyfo).
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 stablelm-3b-4e1t-Q8_0.bin --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 stablelm-3b-4e1t-Q8_0.bin --prompt "who was Joseph Weizenbaum?"
```
### Embeddings Calculation with LLaMA.cpp ###
Text embeddings are calculated with a command similar to
```
./embedding -m stablelm-3b-4e1t-Q8_0.bin --prompt "who was Joseph Weizenbaum?"
```
## Conversion Details ##
Conversion was done using a Docker container based on
`python:3.10.13-slim-bookworm`
After downloading the original model files into a separate directory, the
container was started with
```
docker run --interactive \
--mount type=bind,src=<local-folder>,dst=/llm \
python:3.10.13-slim-bookworm
```
where `<local-folder>` was the path to the folder containing the downloaded
model.
Within the container's terminal, the following commands were issued:
```
apt-get update
apt-get install build-essential git -y
git clone https://github.com/ggerganov/llama.cpp
cd llama.cpp
## Important: uncomment the make command that fits to your host computer!
## on Apple Silicon machines: (see https://github.com/ggerganov/llama.cpp/issues/1655)
# UNAME_M=arm64 UNAME_p=arm LLAMA_NO_METAL=1 make
## otherwise
# make
python3 -m pip install -r requirements.txt
pip install torch transformers
# see https://github.com/ggerganov/llama.cpp/issues/3344
python3 convert-hf-to-gguf.py /llm
mv /llm/ggml-model-f16.gguf /llm/stablelm-3b-4e1t.gguf
# the following command is just an example, modify it as needed
./quantize /llm/stablelm-3b-4e1t.gguf /llm/stablelm-3b-4e1t_Q3_K_M.gguf q3_k_m
```
After conversion, the mounted folder (the one that originally contained the
model only) now also contains all conversions.
The container itself may now be safely deleted - the conversions will remain on
disk.
## License ##
The original "_Model checkpoints are licensed under the Creative Commons license
([CC BY-SA-4.0](https://creativecommons.org/licenses/by-sa/4.0/)). Under this
license, you must give [credit](https://creativecommons.org/licenses/by/4.0/#)
to Stability AI, provide a link to the license, and
[indicate if changes were made](https://creativecommons.org/licenses/by/4.0/#).
You may do so in any reasonable manner, but not in any way that suggests the Stability AI endorses you or your use._"
So, in order to be fair and give credits to whom they belong:
* the original model was created and published by [Stability AI](https://huggingface.co/stabilityai)
* besides quantization, no changes were applied to the model itself