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tensorblock/
tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1-GGUF

Name: tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1-GGUF
Rating: 2.5 (22 reviews)

habanoz/tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1

quantized

OpenAssistant/oasst_top1_2023-08-25

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habanoz/tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1 - GGUF

This repo contains GGUF format model files for habanoz/tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.

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## Prompt template

Model file specification

Filename	Quant type	File Size	Description
tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1-Q2_K.gguf	Q2_K	0.432 GB	smallest, significant quality loss - not recommended for most purposes
tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1-Q3_K_S.gguf	Q3_K_S	0.499 GB	very small, high quality loss
tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1-Q3_K_M.gguf	Q3_K_M	0.548 GB	very small, high quality loss
tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1-Q3_K_L.gguf	Q3_K_L	0.592 GB	small, substantial quality loss
tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1-Q4_0.gguf	Q4_0	0.637 GB	legacy; small, very high quality loss - prefer using Q3_K_M
tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1-Q4_K_S.gguf	Q4_K_S	0.640 GB	small, greater quality loss
tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1-Q4_K_M.gguf	Q4_K_M	0.668 GB	medium, balanced quality - recommended
tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1-Q5_0.gguf	Q5_0	0.766 GB	legacy; medium, balanced quality - prefer using Q4_K_M
tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1-Q5_K_S.gguf	Q5_K_S	0.766 GB	large, low quality loss - recommended
tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1-Q5_K_M.gguf	Q5_K_M	0.782 GB	large, very low quality loss - recommended
tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1-Q6_K.gguf	Q6_K	0.903 GB	very large, extremely low quality loss
tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1-Q8_0.gguf	Q8_0	1.170 GB	very large, extremely low quality loss - not recommended

Downloading instruction

Command line

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1-GGUF --include "tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1-Q2_K.gguf" --local-dir MY_LOCAL_DIR

If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:

huggingface-cli download tensorblock/tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'