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RichardErkhov/
weiser_-_82M-0.4-gguf

Name: weiser_-_82M-0.4-gguf
Availability: InStock

endpoints_compatible

gguf

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82M-0.4 - GGUF

Model creator: https://huggingface.co/weiser/
Original model: https://huggingface.co/weiser/82M-0.4/

Name	Quant method	Size
82M-0.4.Q2_K.gguf	Q2_K	0.08GB
82M-0.4.IQ3_XS.gguf	IQ3_XS	0.08GB
82M-0.4.IQ3_S.gguf	IQ3_S	0.08GB
82M-0.4.Q3_K_S.gguf	Q3_K_S	0.08GB
82M-0.4.IQ3_M.gguf	IQ3_M	0.08GB
82M-0.4.Q3_K.gguf	Q3_K	0.08GB
82M-0.4.Q3_K_M.gguf	Q3_K_M	0.08GB
82M-0.4.Q3_K_L.gguf	Q3_K_L	0.08GB
82M-0.4.IQ4_XS.gguf	IQ4_XS	0.08GB
82M-0.4.Q4_0.gguf	Q4_0	0.08GB
82M-0.4.IQ4_NL.gguf	IQ4_NL	0.08GB
82M-0.4.Q4_K_S.gguf	Q4_K_S	0.09GB
82M-0.4.Q4_K.gguf	Q4_K	0.09GB
82M-0.4.Q4_K_M.gguf	Q4_K_M	0.09GB
82M-0.4.Q4_1.gguf	Q4_1	0.08GB
82M-0.4.Q5_0.gguf	Q5_0	0.09GB
82M-0.4.Q5_K_S.gguf	Q5_K_S	0.09GB
82M-0.4.Q5_K.gguf	Q5_K	0.1GB
82M-0.4.Q5_K_M.gguf	Q5_K_M	0.1GB
82M-0.4.Q5_1.gguf	Q5_1	0.09GB
82M-0.4.Q6_K.gguf	Q6_K	0.11GB
82M-0.4.Q8_0.gguf	Q8_0	0.12GB

Original model description:

license: apache-2.0 datasets:

HuggingFaceFW/fineweb language:
en library_name: transformers tags:
IoT
sensor
embedded

TinyLLM

Overview

This repository hosts a small language model developed as part of the TinyLLM framework ([arxiv link]). These models are specifically designed and fine-tuned with sensor data to support embedded sensing applications. They enable locally hosted language models on low-computing-power devices, such as single-board computers. The models, based on the GPT-2 architecture, are trained using Nvidia's H100 GPUs. This repo provides base models that can be further fine-tuned for specific downstream tasks related to embedded sensing.

Model Information

Parameters: 82M (Hidden Size = 640)
Architecture: Decoder-only transformer
Training Data: Up to 10B tokens from the SHL and Fineweb datasets, combined in a 4:6 ratio
Input and Output Modality: Text
Context Length: 1024

Acknowledgements

We want to acknowledge the open-source frameworks llm.c and llama.cpp and the sensor dataset provided by SHL, which were instrumental in training and testing these models.

Usage

The model can be used in two primary ways:

With Hugging Face’s Transformers Library

python
1from transformers import pipeline 2import torch 3 4path = "tinyllm/82M-0.4" 5prompt = "The sea is blue but it's his red sea" 6 7generator = pipeline("text-generation", model=path,max_new_tokens = 30, repetition_penalty=1.3, model_kwargs={"torch_dtype": torch.bfloat16}, device_map="auto") 8print(generator(prompt)[0]['generated_text'])
With llama.cpp Generate a GGUF model file using this tool and use the generated GGUF file for inferencing.

python3 convert_hf_to_gguf.py models/mymodel/

Disclaimer

This model is intended solely for research purposes.

RichardErkhov/weiser_-_82M-0.4-gguf