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---
language:
- en
license: apache-2.0
library_name: transformers
tags:
- qwen
- qwen2.5
- finetune
- dpo
- orpo
- qwen2
- chat
- conversational
- instruct
- storywriting
- roleplay
- novelwriting
- TensorBlock
- GGUF
base_model: v000000/Qwen2.5-Lumen-14B
datasets:
- jondurbin/gutenberg-dpo-v0.1
- Qwen/Qwen2.5-14B-Instruct
- HuggingFaceH4/ultrafeedback_binarized
pipeline_tag: text-generation
model-index:
- name: Qwen2.5-Lumen-14B
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: 80.64
name: strict accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=v000000/Qwen2.5-Lumen-14B
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: 48.51
name: normalized accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=v000000/Qwen2.5-Lumen-14B
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: 0.0
name: exact match
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=v000000/Qwen2.5-Lumen-14B
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: 10.4
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=v000000/Qwen2.5-Lumen-14B
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: 10.29
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=v000000/Qwen2.5-Lumen-14B
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: 43.36
name: accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=v000000/Qwen2.5-Lumen-14B
name: Open LLM Leaderboard
---
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<div style="display: flex; justify-content: space-between; width: 100%;">
<div style="display: flex; flex-direction: column; align-items: flex-start;">
<p style="margin-top: 0.5em; margin-bottom: 0em;">
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>
</p>
</div>
</div>
## v000000/Qwen2.5-Lumen-14B - GGUF
This repo contains GGUF format model files for [v000000/Qwen2.5-Lumen-14B](https://huggingface.co/v000000/Qwen2.5-Lumen-14B).
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 |
| -------- | ---------- | --------- | ----------- |
| [Qwen2.5-Lumen-14B-Q2_K.gguf](https://huggingface.co/tensorblock/Qwen2.5-Lumen-14B-GGUF/blob/main/Qwen2.5-Lumen-14B-Q2_K.gguf) | Q2_K | 5.374 GB | smallest, significant quality loss - not recommended for most purposes |
| [Qwen2.5-Lumen-14B-Q3_K_S.gguf](https://huggingface.co/tensorblock/Qwen2.5-Lumen-14B-GGUF/blob/main/Qwen2.5-Lumen-14B-Q3_K_S.gguf) | Q3_K_S | 6.202 GB | very small, high quality loss |
| [Qwen2.5-Lumen-14B-Q3_K_M.gguf](https://huggingface.co/tensorblock/Qwen2.5-Lumen-14B-GGUF/blob/main/Qwen2.5-Lumen-14B-Q3_K_M.gguf) | Q3_K_M | 6.835 GB | very small, high quality loss |
| [Qwen2.5-Lumen-14B-Q3_K_L.gguf](https://huggingface.co/tensorblock/Qwen2.5-Lumen-14B-GGUF/blob/main/Qwen2.5-Lumen-14B-Q3_K_L.gguf) | Q3_K_L | 7.381 GB | small, substantial quality loss |
| [Qwen2.5-Lumen-14B-Q4_0.gguf](https://huggingface.co/tensorblock/Qwen2.5-Lumen-14B-GGUF/blob/main/Qwen2.5-Lumen-14B-Q4_0.gguf) | Q4_0 | 7.933 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [Qwen2.5-Lumen-14B-Q4_K_S.gguf](https://huggingface.co/tensorblock/Qwen2.5-Lumen-14B-GGUF/blob/main/Qwen2.5-Lumen-14B-Q4_K_S.gguf) | Q4_K_S | 7.985 GB | small, greater quality loss |
| [Qwen2.5-Lumen-14B-Q4_K_M.gguf](https://huggingface.co/tensorblock/Qwen2.5-Lumen-14B-GGUF/blob/main/Qwen2.5-Lumen-14B-Q4_K_M.gguf) | Q4_K_M | 8.371 GB | medium, balanced quality - recommended |
| [Qwen2.5-Lumen-14B-Q5_0.gguf](https://huggingface.co/tensorblock/Qwen2.5-Lumen-14B-GGUF/blob/main/Qwen2.5-Lumen-14B-Q5_0.gguf) | Q5_0 | 9.561 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [Qwen2.5-Lumen-14B-Q5_K_S.gguf](https://huggingface.co/tensorblock/Qwen2.5-Lumen-14B-GGUF/blob/main/Qwen2.5-Lumen-14B-Q5_K_S.gguf) | Q5_K_S | 9.561 GB | large, low quality loss - recommended |
| [Qwen2.5-Lumen-14B-Q5_K_M.gguf](https://huggingface.co/tensorblock/Qwen2.5-Lumen-14B-GGUF/blob/main/Qwen2.5-Lumen-14B-Q5_K_M.gguf) | Q5_K_M | 9.787 GB | large, very low quality loss - recommended |
| [Qwen2.5-Lumen-14B-Q6_K.gguf](https://huggingface.co/tensorblock/Qwen2.5-Lumen-14B-GGUF/blob/main/Qwen2.5-Lumen-14B-Q6_K.gguf) | Q6_K | 11.292 GB | very large, extremely low quality loss |
| [Qwen2.5-Lumen-14B-Q8_0.gguf](https://huggingface.co/tensorblock/Qwen2.5-Lumen-14B-GGUF/blob/main/Qwen2.5-Lumen-14B-Q8_0.gguf) | Q8_0 | 14.623 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/Qwen2.5-Lumen-14B-GGUF --include "Qwen2.5-Lumen-14B-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/Qwen2.5-Lumen-14B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```
|