metadata
license: apache-2.0
library_name: transformers
tags:
- qwen2
- qwen2.5
- dpo
- chat
- conversational
- finetune
- TensorBlock
- GGUF
base_model: v000000/Qwen2.5-14B-Gutenberg-1e-Delta
datasets:
- jondurbin/gutenberg-dpo-v0.1
model-index:
- name: Qwen2.5-14B-Gutenberg-1e-Delta
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: HuggingFaceH4/ifeval
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 80.45
name: strict accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=v000000/Qwen2.5-14B-Gutenberg-1e-Delta
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: BBH
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 48.62
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=v000000/Qwen2.5-14B-Gutenberg-1e-Delta
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: hendrycks/competition_math
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 0
name: exact match
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=v000000/Qwen2.5-14B-Gutenberg-1e-Delta
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 10.51
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=v000000/Qwen2.5-14B-Gutenberg-1e-Delta
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 9.38
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=v000000/Qwen2.5-14B-Gutenberg-1e-Delta
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 43.67
name: accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=v000000/Qwen2.5-14B-Gutenberg-1e-Delta
name: Open LLM Leaderboard
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
v000000/Qwen2.5-14B-Gutenberg-1e-Delta - GGUF
This repo contains GGUF format model files for v000000/Qwen2.5-14B-Gutenberg-1e-Delta.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.
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 |
---|---|---|---|
Qwen2.5-14B-Gutenberg-1e-Delta-Q2_K.gguf | Q2_K | 5.374 GB | smallest, significant quality loss - not recommended for most purposes |
Qwen2.5-14B-Gutenberg-1e-Delta-Q3_K_S.gguf | Q3_K_S | 6.202 GB | very small, high quality loss |
Qwen2.5-14B-Gutenberg-1e-Delta-Q3_K_M.gguf | Q3_K_M | 6.835 GB | very small, high quality loss |
Qwen2.5-14B-Gutenberg-1e-Delta-Q3_K_L.gguf | Q3_K_L | 7.381 GB | small, substantial quality loss |
Qwen2.5-14B-Gutenberg-1e-Delta-Q4_0.gguf | Q4_0 | 7.933 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
Qwen2.5-14B-Gutenberg-1e-Delta-Q4_K_S.gguf | Q4_K_S | 7.985 GB | small, greater quality loss |
Qwen2.5-14B-Gutenberg-1e-Delta-Q4_K_M.gguf | Q4_K_M | 8.371 GB | medium, balanced quality - recommended |
Qwen2.5-14B-Gutenberg-1e-Delta-Q5_0.gguf | Q5_0 | 9.561 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
Qwen2.5-14B-Gutenberg-1e-Delta-Q5_K_S.gguf | Q5_K_S | 9.561 GB | large, low quality loss - recommended |
Qwen2.5-14B-Gutenberg-1e-Delta-Q5_K_M.gguf | Q5_K_M | 9.787 GB | large, very low quality loss - recommended |
Qwen2.5-14B-Gutenberg-1e-Delta-Q6_K.gguf | Q6_K | 11.292 GB | very large, extremely low quality loss |
Qwen2.5-14B-Gutenberg-1e-Delta-Q8_0.gguf | Q8_0 | 14.623 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/Qwen2.5-14B-Gutenberg-1e-Delta-GGUF --include "Qwen2.5-14B-Gutenberg-1e-Delta-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/Qwen2.5-14B-Gutenberg-1e-Delta-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'