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Replete-AI_-_Replete-LLM-V2.5-Qwen-14b-gguf
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Quantization made by Richard Erkhov.

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Replete-LLM-V2.5-Qwen-14b - GGUF
- Model creator: https://huggingface.co/Replete-AI/
- Original model: https://huggingface.co/Replete-AI/Replete-LLM-V2.5-Qwen-14b/


| Name | Quant method | Size |
| ---- | ---- | ---- |
| [Replete-LLM-V2.5-Qwen-14b.Q2_K.gguf](https://huggingface.co/RichardErkhov/Replete-AI_-_Replete-LLM-V2.5-Qwen-14b-gguf/blob/main/Replete-LLM-V2.5-Qwen-14b.Q2_K.gguf) | Q2_K | 5.37GB |
| [Replete-LLM-V2.5-Qwen-14b.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/Replete-AI_-_Replete-LLM-V2.5-Qwen-14b-gguf/blob/main/Replete-LLM-V2.5-Qwen-14b.IQ3_XS.gguf) | IQ3_XS | 5.94GB |
| [Replete-LLM-V2.5-Qwen-14b.IQ3_S.gguf](https://huggingface.co/RichardErkhov/Replete-AI_-_Replete-LLM-V2.5-Qwen-14b-gguf/blob/main/Replete-LLM-V2.5-Qwen-14b.IQ3_S.gguf) | IQ3_S | 6.23GB |
| [Replete-LLM-V2.5-Qwen-14b.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/Replete-AI_-_Replete-LLM-V2.5-Qwen-14b-gguf/blob/main/Replete-LLM-V2.5-Qwen-14b.Q3_K_S.gguf) | Q3_K_S | 6.2GB |
| [Replete-LLM-V2.5-Qwen-14b.IQ3_M.gguf](https://huggingface.co/RichardErkhov/Replete-AI_-_Replete-LLM-V2.5-Qwen-14b-gguf/blob/main/Replete-LLM-V2.5-Qwen-14b.IQ3_M.gguf) | IQ3_M | 6.44GB |
| [Replete-LLM-V2.5-Qwen-14b.Q3_K.gguf](https://huggingface.co/RichardErkhov/Replete-AI_-_Replete-LLM-V2.5-Qwen-14b-gguf/blob/main/Replete-LLM-V2.5-Qwen-14b.Q3_K.gguf) | Q3_K | 6.84GB |
| [Replete-LLM-V2.5-Qwen-14b.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/Replete-AI_-_Replete-LLM-V2.5-Qwen-14b-gguf/blob/main/Replete-LLM-V2.5-Qwen-14b.Q3_K_M.gguf) | Q3_K_M | 6.84GB |
| [Replete-LLM-V2.5-Qwen-14b.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/Replete-AI_-_Replete-LLM-V2.5-Qwen-14b-gguf/blob/main/Replete-LLM-V2.5-Qwen-14b.Q3_K_L.gguf) | Q3_K_L | 7.38GB |
| [Replete-LLM-V2.5-Qwen-14b.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/Replete-AI_-_Replete-LLM-V2.5-Qwen-14b-gguf/blob/main/Replete-LLM-V2.5-Qwen-14b.IQ4_XS.gguf) | IQ4_XS | 7.62GB |
| [Replete-LLM-V2.5-Qwen-14b.Q4_0.gguf](https://huggingface.co/RichardErkhov/Replete-AI_-_Replete-LLM-V2.5-Qwen-14b-gguf/blob/main/Replete-LLM-V2.5-Qwen-14b.Q4_0.gguf) | Q4_0 | 7.93GB |
| [Replete-LLM-V2.5-Qwen-14b.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/Replete-AI_-_Replete-LLM-V2.5-Qwen-14b-gguf/blob/main/Replete-LLM-V2.5-Qwen-14b.IQ4_NL.gguf) | IQ4_NL | 8.01GB |
| [Replete-LLM-V2.5-Qwen-14b.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/Replete-AI_-_Replete-LLM-V2.5-Qwen-14b-gguf/blob/main/Replete-LLM-V2.5-Qwen-14b.Q4_K_S.gguf) | Q4_K_S | 7.98GB |
| [Replete-LLM-V2.5-Qwen-14b.Q4_K.gguf](https://huggingface.co/RichardErkhov/Replete-AI_-_Replete-LLM-V2.5-Qwen-14b-gguf/blob/main/Replete-LLM-V2.5-Qwen-14b.Q4_K.gguf) | Q4_K | 8.37GB |
| [Replete-LLM-V2.5-Qwen-14b.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/Replete-AI_-_Replete-LLM-V2.5-Qwen-14b-gguf/blob/main/Replete-LLM-V2.5-Qwen-14b.Q4_K_M.gguf) | Q4_K_M | 8.37GB |
| [Replete-LLM-V2.5-Qwen-14b.Q4_1.gguf](https://huggingface.co/RichardErkhov/Replete-AI_-_Replete-LLM-V2.5-Qwen-14b-gguf/blob/main/Replete-LLM-V2.5-Qwen-14b.Q4_1.gguf) | Q4_1 | 8.75GB |
| [Replete-LLM-V2.5-Qwen-14b.Q5_0.gguf](https://huggingface.co/RichardErkhov/Replete-AI_-_Replete-LLM-V2.5-Qwen-14b-gguf/blob/main/Replete-LLM-V2.5-Qwen-14b.Q5_0.gguf) | Q5_0 | 9.56GB |
| [Replete-LLM-V2.5-Qwen-14b.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/Replete-AI_-_Replete-LLM-V2.5-Qwen-14b-gguf/blob/main/Replete-LLM-V2.5-Qwen-14b.Q5_K_S.gguf) | Q5_K_S | 9.56GB |
| [Replete-LLM-V2.5-Qwen-14b.Q5_K.gguf](https://huggingface.co/RichardErkhov/Replete-AI_-_Replete-LLM-V2.5-Qwen-14b-gguf/blob/main/Replete-LLM-V2.5-Qwen-14b.Q5_K.gguf) | Q5_K | 9.79GB |
| [Replete-LLM-V2.5-Qwen-14b.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/Replete-AI_-_Replete-LLM-V2.5-Qwen-14b-gguf/blob/main/Replete-LLM-V2.5-Qwen-14b.Q5_K_M.gguf) | Q5_K_M | 9.79GB |
| [Replete-LLM-V2.5-Qwen-14b.Q5_1.gguf](https://huggingface.co/RichardErkhov/Replete-AI_-_Replete-LLM-V2.5-Qwen-14b-gguf/blob/main/Replete-LLM-V2.5-Qwen-14b.Q5_1.gguf) | Q5_1 | 10.38GB |
| [Replete-LLM-V2.5-Qwen-14b.Q6_K.gguf](https://huggingface.co/RichardErkhov/Replete-AI_-_Replete-LLM-V2.5-Qwen-14b-gguf/blob/main/Replete-LLM-V2.5-Qwen-14b.Q6_K.gguf) | Q6_K | 11.29GB |
| [Replete-LLM-V2.5-Qwen-14b.Q8_0.gguf](https://huggingface.co/RichardErkhov/Replete-AI_-_Replete-LLM-V2.5-Qwen-14b-gguf/blob/main/Replete-LLM-V2.5-Qwen-14b.Q8_0.gguf) | Q8_0 | 14.62GB |




Original model description:
---
license: apache-2.0
library_name: transformers
base_model:
- Qwen/Qwen2.5-14B-Instruct
model-index:
- name: Replete-LLM-V2.5-Qwen-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: 58.4
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Replete-AI/Replete-LLM-V2.5-Qwen-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: 49.39
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Replete-AI/Replete-LLM-V2.5-Qwen-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: 15.63
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Replete-AI/Replete-LLM-V2.5-Qwen-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: 16.22
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Replete-AI/Replete-LLM-V2.5-Qwen-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: 18.83
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Replete-AI/Replete-LLM-V2.5-Qwen-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: 48.62
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Replete-AI/Replete-LLM-V2.5-Qwen-14b
      name: Open LLM Leaderboard
---
# Replete-LLM-V2.5-Qwen-14b

![image/png](https://cdn-uploads.huggingface.co/production/uploads/642cc1c253e76b4c2286c58e/ihnWXDEgV-ZKN_B036U1J.png)

Replete-LLM-V2.5-Qwen-14b is a continues finetuned version of Qwen2.5-14B. I noticed recently that the Qwen team did not learn from my methods of continuous finetuning, the great benefits, and no downsides of it. So I took it upon myself to merge the instruct model with the base model myself using the *Ties* merge method

This version of the model shows higher performance than the original instruct and base models. 

Quants:

GGUF: https://huggingface.co/bartowski/Replete-LLM-V2.5-Qwen-14b-GGUF

Benchmarks: 
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Replete-AI__Replete-LLM-V2.5-Qwen-14b)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |34.52|
|IFEval (0-Shot)    |58.40|
|BBH (3-Shot)       |49.39|
|MATH Lvl 5 (4-Shot)|15.63|
|GPQA (0-shot)      |16.22|
|MuSR (0-shot)      |18.83|
|MMLU-PRO (5-shot)  |48.62|