File size: 7,335 Bytes

---
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: ' 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
base_model: 01-ai/Yi-9B
tags:
- TensorBlock
- GGUF
---

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## 01-ai/Yi-9B - GGUF

This repo contains GGUF format model files for [01-ai/Yi-9B](https://huggingface.co/01-ai/Yi-9B).

The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).


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## Prompt template


```

```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [Yi-9B-Q2_K.gguf](https://huggingface.co/tensorblock/Yi-9B-GGUF/blob/main/Yi-9B-Q2_K.gguf) | Q2_K | 3.124 GB | smallest, significant quality loss - not recommended for most purposes |
| [Yi-9B-Q3_K_S.gguf](https://huggingface.co/tensorblock/Yi-9B-GGUF/blob/main/Yi-9B-Q3_K_S.gguf) | Q3_K_S | 3.631 GB | very small, high quality loss |
| [Yi-9B-Q3_K_M.gguf](https://huggingface.co/tensorblock/Yi-9B-GGUF/blob/main/Yi-9B-Q3_K_M.gguf) | Q3_K_M | 4.027 GB | very small, high quality loss |
| [Yi-9B-Q3_K_L.gguf](https://huggingface.co/tensorblock/Yi-9B-GGUF/blob/main/Yi-9B-Q3_K_L.gguf) | Q3_K_L | 4.369 GB | small, substantial quality loss |
| [Yi-9B-Q4_0.gguf](https://huggingface.co/tensorblock/Yi-9B-GGUF/blob/main/Yi-9B-Q4_0.gguf) | Q4_0 | 4.691 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [Yi-9B-Q4_K_S.gguf](https://huggingface.co/tensorblock/Yi-9B-GGUF/blob/main/Yi-9B-Q4_K_S.gguf) | Q4_K_S | 4.724 GB | small, greater quality loss |
| [Yi-9B-Q4_K_M.gguf](https://huggingface.co/tensorblock/Yi-9B-GGUF/blob/main/Yi-9B-Q4_K_M.gguf) | Q4_K_M | 4.963 GB | medium, balanced quality - recommended |
| [Yi-9B-Q5_0.gguf](https://huggingface.co/tensorblock/Yi-9B-GGUF/blob/main/Yi-9B-Q5_0.gguf) | Q5_0 | 5.688 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [Yi-9B-Q5_K_S.gguf](https://huggingface.co/tensorblock/Yi-9B-GGUF/blob/main/Yi-9B-Q5_K_S.gguf) | Q5_K_S | 5.688 GB | large, low quality loss - recommended |
| [Yi-9B-Q5_K_M.gguf](https://huggingface.co/tensorblock/Yi-9B-GGUF/blob/main/Yi-9B-Q5_K_M.gguf) | Q5_K_M | 5.828 GB | large, very low quality loss - recommended |
| [Yi-9B-Q6_K.gguf](https://huggingface.co/tensorblock/Yi-9B-GGUF/blob/main/Yi-9B-Q6_K.gguf) | Q6_K | 6.748 GB | very large, extremely low quality loss |
| [Yi-9B-Q8_0.gguf](https://huggingface.co/tensorblock/Yi-9B-GGUF/blob/main/Yi-9B-Q8_0.gguf) | Q8_0 | 8.739 GB | very large, extremely low quality loss - not recommended |


## Downloading instruction

### Command line

Firstly, install Huggingface Client

```shell
pip install -U "huggingface_hub[cli]"
```

Then, downoad the individual model file the a local directory

```shell
huggingface-cli download tensorblock/Yi-9B-GGUF --include "Yi-9B-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:

```shell
huggingface-cli download tensorblock/Yi-9B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```