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RichardErkhov/
unsloth_-_Phi-3-mini-4k-instruct-gguf

Name: unsloth_-_Phi-3-mini-4k-instruct-gguf
Availability: InStock

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Quantization made by Richard Erkhov.

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Phi-3-mini-4k-instruct - GGUF

Model creator: https://huggingface.co/unsloth/
Original model: https://huggingface.co/unsloth/Phi-3-mini-4k-instruct/

Name	Quant method	Size
Phi-3-mini-4k-instruct.Q2_K.gguf	Q2_K	1.35GB
Phi-3-mini-4k-instruct.IQ3_XS.gguf	IQ3_XS	1.49GB
Phi-3-mini-4k-instruct.IQ3_S.gguf	IQ3_S	1.57GB
Phi-3-mini-4k-instruct.Q3_K_S.gguf	Q3_K_S	1.57GB
Phi-3-mini-4k-instruct.IQ3_M.gguf	IQ3_M	1.65GB
Phi-3-mini-4k-instruct.Q3_K.gguf	Q3_K	1.75GB
Phi-3-mini-4k-instruct.Q3_K_M.gguf	Q3_K_M	1.75GB
Phi-3-mini-4k-instruct.Q3_K_L.gguf	Q3_K_L	1.9GB
Phi-3-mini-4k-instruct.IQ4_XS.gguf	IQ4_XS	1.93GB
Phi-3-mini-4k-instruct.Q4_0.gguf	Q4_0	2.03GB
Phi-3-mini-4k-instruct.IQ4_NL.gguf	IQ4_NL	2.04GB
Phi-3-mini-4k-instruct.Q4_K_S.gguf	Q4_K_S	2.04GB
Phi-3-mini-4k-instruct.Q4_K.gguf	Q4_K	2.16GB
Phi-3-mini-4k-instruct.Q4_K_M.gguf	Q4_K_M	2.16GB
Phi-3-mini-4k-instruct.Q4_1.gguf	Q4_1	2.24GB
Phi-3-mini-4k-instruct.Q5_0.gguf	Q5_0	2.46GB
Phi-3-mini-4k-instruct.Q5_K_S.gguf	Q5_K_S	2.46GB
Phi-3-mini-4k-instruct.Q5_K.gguf	Q5_K	2.53GB
Phi-3-mini-4k-instruct.Q5_K_M.gguf	Q5_K_M	2.53GB
Phi-3-mini-4k-instruct.Q5_1.gguf	Q5_1	2.68GB
Phi-3-mini-4k-instruct.Q6_K.gguf	Q6_K	2.92GB
Phi-3-mini-4k-instruct.Q8_0.gguf	Q8_0	3.78GB

Original model description:

language:

en library_name: transformers license: mit tags:
unsloth
transformers
phi3
phi

Reminder to use the dev version Transformers:

pip install git+https://github.com/huggingface/transformers.git

Finetune Phi-3, Llama 3, Gemma 2, Mistral 2-5x faster with 70% less memory via Unsloth!

Directly quantized 4bit model with bitsandbytes. We Mistralfied the model to ensure it could be used on many platforms

We have a Google Colab Tesla T4 notebook for Phi-3 (mini) here: https://colab.research.google.com/drive/1vIrqH5uYDQwsJ4-OO3DErvuv4pBgVwk4?usp=sharing And another notebook for Phi-3 (medium) here: https://colab.research.google.com/drive/1hhdhBa1j_hsymiW9m-WzxQtgqTH_NHqi?usp=sharing

✨ 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 2 (9B)	▶️ Start on Colab	2x faster	63% less
Mistral (9B)	▶️ Start on Colab	2.2x faster	62% less
Phi 3 (mini)	▶️ Start on Colab	2x faster	50% less
Phi 3 (medium)	▶️ Start on Colab	2x faster	50% 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_-_Phi-3-mini-4k-instruct-gguf

Original model description:

Reminder to use the dev version Transformers:

Finetune Phi-3, Llama 3, Gemma 2, Mistral 2-5x faster with 70% less memory via Unsloth!

✨ Finetune for Free

RichardErkhov/
unsloth_-_Phi-3-mini-4k-instruct-gguf