metadata
language:
- en
- ko
library_name: transformers
tags:
- pytorch
- Yi-Ko
- 01-ai
- Yi
- TensorBlock
- GGUF
extra_gated_heading: Access beomi/Yi-Ko-6B on Hugging Face
extra_gated_button_content: Submit
extra_gated_fields:
I agree to share my name, email address and username: checkbox
I confirm that I understand this project is for research purposes only, and confirm that I agree to follow the LICENSE of this model: checkbox
pipeline_tag: text-generation
inference: false
license: apache-2.0
base_model: beomi/Yi-Ko-6B
model-index:
- name: Yi-Ko-6B
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: 48.89
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=beomi/Yi-Ko-6B
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: 74.48
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=beomi/Yi-Ko-6B
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: 55.72
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=beomi/Yi-Ko-6B
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: 37.09
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=beomi/Yi-Ko-6B
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: 72.93
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=beomi/Yi-Ko-6B
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: 12.51
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=beomi/Yi-Ko-6B
name: Open LLM Leaderboard
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
beomi/Yi-Ko-6B - GGUF
This repo contains GGUF format model files for beomi/Yi-Ko-6B.
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-Ko-6B-Q2_K.gguf | Q2_K | 2.240 GB | smallest, significant quality loss - not recommended for most purposes |
Yi-Ko-6B-Q3_K_S.gguf | Q3_K_S | 2.592 GB | very small, high quality loss |
Yi-Ko-6B-Q3_K_M.gguf | Q3_K_M | 2.857 GB | very small, high quality loss |
Yi-Ko-6B-Q3_K_L.gguf | Q3_K_L | 3.084 GB | small, substantial quality loss |
Yi-Ko-6B-Q4_0.gguf | Q4_0 | 3.317 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
Yi-Ko-6B-Q4_K_S.gguf | Q4_K_S | 3.339 GB | small, greater quality loss |
Yi-Ko-6B-Q4_K_M.gguf | Q4_K_M | 3.498 GB | medium, balanced quality - recommended |
Yi-Ko-6B-Q5_0.gguf | Q5_0 | 3.999 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
Yi-Ko-6B-Q5_K_S.gguf | Q5_K_S | 3.999 GB | large, low quality loss - recommended |
Yi-Ko-6B-Q5_K_M.gguf | Q5_K_M | 4.092 GB | large, very low quality loss - recommended |
Yi-Ko-6B-Q6_K.gguf | Q6_K | 4.724 GB | very large, extremely low quality loss |
Yi-Ko-6B-Q8_0.gguf | Q8_0 | 6.117 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-Ko-6B-GGUF --include "Yi-Ko-6B-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-Ko-6B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'