You can deploy this model and start earning money today!

RichardErkhov/
unsloth_-_Qwen2-0.5B-Instruct-awq

Name: unsloth_-_Qwen2-0.5B-Instruct-awq
Availability: InStock

Views

No views yet

Quantization made by Richard Erkhov.

Github

Discord

Request more models

Qwen2-0.5B-Instruct - AWQ

Model creator: https://huggingface.co/unsloth/
Original model: https://huggingface.co/unsloth/Qwen2-0.5B-Instruct/

Original model description:

language:

en library_name: transformers license: apache-2.0 tags:
unsloth
transformers
qwen2

Finetune Mistral, Gemma, Llama 2-5x faster with 70% less memory via Unsloth!

We have a Google Colab Tesla T4 notebook for Qwen2 7b here: https://colab.research.google.com/drive/1mvwsIQWDs2EdZxZQF9pRGnnOvE86MVvR?usp=sharing And a Colab notebook for Qwen2 0.5b and another for Qwen2 1.5b

✨ Finetune for Free

All notebooks are beginner friendly! Add your dataset, click "Run All", and you'll get a 2x faster finetuned model which can be exported to GGUF, vLLM or uploaded to Hugging Face.

Unsloth supports	Free Notebooks	Performance	Memory use
Llama-3 8b	▶️ Start on Colab	2.4x faster	58% less
Gemma 7b	▶️ Start on Colab	2.4x faster	58% less
Mistral 7b	▶️ Start on Colab	2.2x faster	62% less
Llama-2 7b	▶️ Start on Colab	2.2x faster	43% less
TinyLlama	▶️ Start on Colab	3.9x faster	74% less
CodeLlama 34b A100	▶️ Start on Colab	1.9x faster	27% less
Mistral 7b 1xT4	▶️ Start on Kaggle	5x faster*	62% less
DPO - Zephyr	▶️ Start on Colab	1.9x faster	19% less

This conversational notebook is useful for ShareGPT ChatML / Vicuna templates.
This text completion notebook is for raw text. This DPO notebook replicates Zephyr.
* Kaggle has 2x T4s, but we use 1. Due to overhead, 1x T4 is 5x faster.

RichardErkhov/unsloth_-_Qwen2-0.5B-Instruct-awq

Original model description:

Finetune Mistral, Gemma, Llama 2-5x faster with 70% less memory via Unsloth!

✨ Finetune for Free

RichardErkhov/
unsloth_-_Qwen2-0.5B-Instruct-awq