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---
license: cc
base_model: Walmart-the-bag/Yi-6B-Infinity-Chat
inference: false
tags:
- TensorBlock
- GGUF
model-index:
- name: Yi-6B-Infinity-Chat
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: AI2 Reasoning Challenge (25-Shot)
type: ai2_arc
config: ARC-Challenge
split: test
args:
num_few_shot: 25
metrics:
- type: acc_norm
value: 56.57
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Walmart-the-bag/Yi-6B-Infinity-Chat
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: HellaSwag (10-Shot)
type: hellaswag
split: validation
args:
num_few_shot: 10
metrics:
- type: acc_norm
value: 77.66
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Walmart-the-bag/Yi-6B-Infinity-Chat
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU (5-Shot)
type: cais/mmlu
config: all
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 64.05
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Walmart-the-bag/Yi-6B-Infinity-Chat
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: TruthfulQA (0-shot)
type: truthful_qa
config: multiple_choice
split: validation
args:
num_few_shot: 0
metrics:
- type: mc2
value: 50.75
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Walmart-the-bag/Yi-6B-Infinity-Chat
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Winogrande (5-shot)
type: winogrande
config: winogrande_xl
split: validation
args:
num_few_shot: 5
metrics:
- type: acc
value: 73.95
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Walmart-the-bag/Yi-6B-Infinity-Chat
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GSM8k (5-shot)
type: gsm8k
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 36.01
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Walmart-the-bag/Yi-6B-Infinity-Chat
name: Open LLM Leaderboard
---
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<div style="display: flex; justify-content: space-between; width: 100%;">
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Feedback and support: TensorBlock's <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a>
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## Walmart-the-bag/Yi-6B-Infinity-Chat - GGUF
This repo contains GGUF format model files for [Walmart-the-bag/Yi-6B-Infinity-Chat](https://huggingface.co/Walmart-the-bag/Yi-6B-Infinity-Chat).
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).
<div style="text-align: left; margin: 20px 0;">
<a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
Run them on the TensorBlock client using your local machine ↗
</a>
</div>
## Prompt template
```
<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
```
## Model file specification
| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [Yi-6B-Infinity-Chat-Q2_K.gguf](https://huggingface.co/tensorblock/Yi-6B-Infinity-Chat-GGUF/blob/main/Yi-6B-Infinity-Chat-Q2_K.gguf) | Q2_K | 2.177 GB | smallest, significant quality loss - not recommended for most purposes |
| [Yi-6B-Infinity-Chat-Q3_K_S.gguf](https://huggingface.co/tensorblock/Yi-6B-Infinity-Chat-GGUF/blob/main/Yi-6B-Infinity-Chat-Q3_K_S.gguf) | Q3_K_S | 2.523 GB | very small, high quality loss |
| [Yi-6B-Infinity-Chat-Q3_K_M.gguf](https://huggingface.co/tensorblock/Yi-6B-Infinity-Chat-GGUF/blob/main/Yi-6B-Infinity-Chat-Q3_K_M.gguf) | Q3_K_M | 2.788 GB | very small, high quality loss |
| [Yi-6B-Infinity-Chat-Q3_K_L.gguf](https://huggingface.co/tensorblock/Yi-6B-Infinity-Chat-GGUF/blob/main/Yi-6B-Infinity-Chat-Q3_K_L.gguf) | Q3_K_L | 3.015 GB | small, substantial quality loss |
| [Yi-6B-Infinity-Chat-Q4_0.gguf](https://huggingface.co/tensorblock/Yi-6B-Infinity-Chat-GGUF/blob/main/Yi-6B-Infinity-Chat-Q4_0.gguf) | Q4_0 | 3.241 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [Yi-6B-Infinity-Chat-Q4_K_S.gguf](https://huggingface.co/tensorblock/Yi-6B-Infinity-Chat-GGUF/blob/main/Yi-6B-Infinity-Chat-Q4_K_S.gguf) | Q4_K_S | 3.263 GB | small, greater quality loss |
| [Yi-6B-Infinity-Chat-Q4_K_M.gguf](https://huggingface.co/tensorblock/Yi-6B-Infinity-Chat-GGUF/blob/main/Yi-6B-Infinity-Chat-Q4_K_M.gguf) | Q4_K_M | 3.422 GB | medium, balanced quality - recommended |
| [Yi-6B-Infinity-Chat-Q5_0.gguf](https://huggingface.co/tensorblock/Yi-6B-Infinity-Chat-GGUF/blob/main/Yi-6B-Infinity-Chat-Q5_0.gguf) | Q5_0 | 3.916 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [Yi-6B-Infinity-Chat-Q5_K_S.gguf](https://huggingface.co/tensorblock/Yi-6B-Infinity-Chat-GGUF/blob/main/Yi-6B-Infinity-Chat-Q5_K_S.gguf) | Q5_K_S | 3.916 GB | large, low quality loss - recommended |
| [Yi-6B-Infinity-Chat-Q5_K_M.gguf](https://huggingface.co/tensorblock/Yi-6B-Infinity-Chat-GGUF/blob/main/Yi-6B-Infinity-Chat-Q5_K_M.gguf) | Q5_K_M | 4.009 GB | large, very low quality loss - recommended |
| [Yi-6B-Infinity-Chat-Q6_K.gguf](https://huggingface.co/tensorblock/Yi-6B-Infinity-Chat-GGUF/blob/main/Yi-6B-Infinity-Chat-Q6_K.gguf) | Q6_K | 4.633 GB | very large, extremely low quality loss |
| [Yi-6B-Infinity-Chat-Q8_0.gguf](https://huggingface.co/tensorblock/Yi-6B-Infinity-Chat-GGUF/blob/main/Yi-6B-Infinity-Chat-Q8_0.gguf) | Q8_0 | 6.000 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-6B-Infinity-Chat-GGUF --include "Yi-6B-Infinity-Chat-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-6B-Infinity-Chat-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```
|