metadata
license: apache-2.0
widget:
- example_title: Yi-34B-Chat
text: hi
output:
text: ' Hello! How can I assist you today?'
- example_title: Yi-34B
text: >-
There's a place where time stands still. A place of breath taking wonder,
but also
output:
text: >2-
an eerie sense that something is just not right…
Between the two worlds lies The Forgotten Kingdom - home to creatures
long since thought extinct and ancient magic so strong it defies belief!
Only here can you find what has been lost for centuries: An Elixir Of
Life which will restore youth and vitality if only those who seek its
power are brave enough to face up against all manner of dangers lurking
in this mysterious land! But beware; some say there may even exist
powerful entities beyond our comprehension whose intentions towards
humanity remain unclear at best ---- they might want nothing more than
destruction itself rather then anything else from their quest after
immortality (and maybe someone should tell them about modern medicine)?
In any event though – one thing remains true regardless : whether or not
success comes easy depends entirely upon how much effort we put into
conquering whatever challenges lie ahead along with having faith deep
down inside ourselves too ;) So let’s get started now shall We?
pipeline_tag: text-generation
tags:
- TensorBlock
- GGUF
base_model: 01-ai/Yi-9B-200K
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
01-ai/Yi-9B-200K - GGUF
This repo contains GGUF format model files for 01-ai/Yi-9B-200K.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.
Prompt template
Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| Yi-9B-200K-Q2_K.gguf | Q2_K | 3.124 GB | smallest, significant quality loss - not recommended for most purposes |
| Yi-9B-200K-Q3_K_S.gguf | Q3_K_S | 3.631 GB | very small, high quality loss |
| Yi-9B-200K-Q3_K_M.gguf | Q3_K_M | 4.027 GB | very small, high quality loss |
| Yi-9B-200K-Q3_K_L.gguf | Q3_K_L | 4.369 GB | small, substantial quality loss |
| Yi-9B-200K-Q4_0.gguf | Q4_0 | 4.691 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| Yi-9B-200K-Q4_K_S.gguf | Q4_K_S | 4.724 GB | small, greater quality loss |
| Yi-9B-200K-Q4_K_M.gguf | Q4_K_M | 4.963 GB | medium, balanced quality - recommended |
| Yi-9B-200K-Q5_0.gguf | Q5_0 | 5.688 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| Yi-9B-200K-Q5_K_S.gguf | Q5_K_S | 5.688 GB | large, low quality loss - recommended |
| Yi-9B-200K-Q5_K_M.gguf | Q5_K_M | 5.828 GB | large, very low quality loss - recommended |
| Yi-9B-200K-Q6_K.gguf | Q6_K | 6.748 GB | very large, extremely low quality loss |
| Yi-9B-200K-Q8_0.gguf | Q8_0 | 8.739 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/Yi-9B-200K-GGUF --include "Yi-9B-200K-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/Yi-9B-200K-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'