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---
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3 |
+
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+
language:
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5 |
+
- en
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6 |
+
license: apache-2.0
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7 |
+
library_name: transformers
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8 |
+
tags:
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9 |
+
- merge
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10 |
+
- mergekit
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11 |
+
- lazymergekit
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12 |
+
- bfloat16
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+
- roleplay
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+
- creative
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15 |
+
- instruct
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16 |
+
- anvita
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+
- qwen
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+
- nerd
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+
- homer
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+
- Qandora
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+
base_model:
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+
- bunnycore/Qandora-2.5-7B-Creative
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+
- allknowingroger/HomerSlerp1-7B
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+
- sethuiyer/Qwen2.5-7B-Anvita
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+
- fblgit/cybertron-v4-qw7B-MGS
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+
- jeffmeloy/Qwen2.5-7B-nerd-uncensored-v1.0
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+
- newsbang/Homer-v0.5-Qwen2.5-7B
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+
pipeline_tag: text-generation
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+
model-index:
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+
- name: Qwen2.5-7B-HomerAnvita-NerdMix
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+
results:
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+
- task:
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+
type: text-generation
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+
name: Text Generation
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+
dataset:
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+
name: IFEval (0-Shot)
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+
type: HuggingFaceH4/ifeval
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+
args:
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+
num_few_shot: 0
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+
metrics:
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+
- type: inst_level_strict_acc and prompt_level_strict_acc
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+
value: 77.08
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+
name: strict accuracy
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+
source:
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+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix
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+
name: Open LLM Leaderboard
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+
- task:
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+
type: text-generation
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+
name: Text Generation
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+
dataset:
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+
name: BBH (3-Shot)
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+
type: BBH
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+
args:
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+
num_few_shot: 3
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+
metrics:
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+
- type: acc_norm
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+
value: 36.58
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+
name: normalized accuracy
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+
source:
|
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+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix
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+
name: Open LLM Leaderboard
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+
- task:
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+
type: text-generation
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+
name: Text Generation
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+
dataset:
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name: MATH Lvl 5 (4-Shot)
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+
type: hendrycks/competition_math
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+
args:
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+
num_few_shot: 4
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+
metrics:
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+
- type: exact_match
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+
value: 29.53
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+
name: exact match
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+
source:
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+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix
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name: Open LLM Leaderboard
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+
- task:
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+
type: text-generation
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+
name: Text Generation
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+
dataset:
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+
name: GPQA (0-shot)
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+
type: Idavidrein/gpqa
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+
args:
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+
num_few_shot: 0
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+
metrics:
|
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+
- type: acc_norm
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+
value: 9.28
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+
name: acc_norm
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+
source:
|
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+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix
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name: Open LLM Leaderboard
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+
- task:
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+
type: text-generation
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+
name: Text Generation
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+
dataset:
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+
name: MuSR (0-shot)
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+
type: TAUR-Lab/MuSR
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+
args:
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+
num_few_shot: 0
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+
metrics:
|
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+
- type: acc_norm
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+
value: 14.41
|
103 |
+
name: acc_norm
|
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+
source:
|
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+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix
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+
name: Open LLM Leaderboard
|
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+
- task:
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+
type: text-generation
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+
name: Text Generation
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+
dataset:
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name: MMLU-PRO (5-shot)
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+
type: TIGER-Lab/MMLU-Pro
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+
config: main
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+
split: test
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+
args:
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+
num_few_shot: 5
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+
metrics:
|
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+
- type: acc
|
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+
value: 38.13
|
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+
name: accuracy
|
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+
source:
|
122 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix
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+
name: Open LLM Leaderboard
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+
|
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+
---
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+
|
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+
[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)
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+
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+
# QuantFactory/Qwen2.5-7B-HomerAnvita-NerdMix-GGUF
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This is quantized version of [ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix](https://huggingface.co/ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix) created using llama.cpp
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# Original Model Card
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# ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix
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**ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix** is an advanced language model meticulously crafted by merging five pre-trained models using the powerful [mergekit](https://github.com/cg123/mergekit) framework. This fusion leverages the **Model Stock** merge method to combine the creative prowess of **Qandora**, the instructive capabilities of **Qwen-Instruct-Fusion**, the sophisticated blending of **HomerSlerp1**, the mathematical precision of **Cybertron-MGS**, and the uncensored expertise of **Qwen-Nerd**. The resulting model excels in creative text generation, contextual understanding, technical reasoning, and dynamic conversational interactions.
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## π Merged Models
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This model merge incorporates the following:
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- [**bunnycore/Qandora-2.5-7B-Creative**](https://huggingface.co/bunnycore/Qandora-2.5-7B-Creative): Specializes in creative text generation, enhancing the model's ability to produce imaginative and diverse content.
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- [**allknowingroger/HomerSlerp1-7B**](https://huggingface.co/allknowingroger/HomerSlerp1-7B): Utilizes spherical linear interpolation (SLERP) to blend model weights smoothly, ensuring a harmonious integration of different model attributes.
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- [**sethuiyer/Qwen2.5-7B-Anvita**](https://huggingface.co/sethuiyer/Qwen2.5-7B-Anvita): Focuses on instruction-following capabilities, improving the model's performance in understanding and executing user commands.
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- [**fblgit/cybertron-v4-qw7B-MGS**](https://huggingface.co/fblgit/cybertron-v4-qw7B-MGS): Enhances mathematical reasoning and precision, enabling the model to handle complex computational tasks effectively.
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- [**jeffmeloy/Qwen2.5-7B-nerd-uncensored-v1.0**](https://huggingface.co/jeffmeloy/Qwen2.5-7B-nerd-uncensored-v1.0): Provides uncensored expertise and robust technical knowledge, making the model suitable for specialized technical support and information retrieval.
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- [**newsbang/Homer-v0.5-Qwen2.5-7B**](https://huggingface.co/newsbang/Homer-v0.5-Qwen2.5-7B): Acts as the foundational conversational model, providing robust language comprehension and generation capabilities.
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## 𧩠Merge Configuration
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The configuration below outlines how the models are merged using the **Model Stock** method. This approach ensures a balanced and effective integration of the unique strengths from each source model.
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```yaml
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# Merge configuration for ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix using Model Stock
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models:
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- model: bunnycore/Qandora-2.5-7B-Creative
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- model: allknowingroger/HomerSlerp1-7B
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- model: sethuiyer/Qwen2.5-7B-Anvita
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- model: fblgit/cybertron-v4-qw7B-MGS
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- model: jeffmeloy/Qwen2.5-7B-nerd-uncensored-v1.0
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merge_method: model_stock
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base_model: newsbang/Homer-v0.5-Qwen2.5-7B
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normalize: false
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int8_mask: true
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dtype: bfloat16
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```
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### Key Parameters
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- **Merge Method (`merge_method`):** Utilizes the **Model Stock** method, as described in [Model Stock](https://arxiv.org/abs/2403.19522), to effectively combine multiple models by leveraging their strengths.
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- **Models (`models`):** Specifies the list of models to be merged:
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- **bunnycore/Qandora-2.5-7B-Creative:** Enhances creative text generation.
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- **allknowingroger/HomerSlerp1-7B:** Facilitates smooth blending of model weights using SLERP.
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- **sethuiyer/Qwen2.5-7B-Anvita:** Improves instruction-following capabilities.
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- **fblgit/cybertron-v4-qw7B-MGS:** Enhances mathematical reasoning and precision.
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- **jeffmeloy/Qwen2.5-7B-nerd-uncensored-v1.0:** Provides uncensored technical expertise.
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- **Base Model (`base_model`):** Defines the foundational model for the merge, which is **newsbang/Homer-v0.5-Qwen2.5-7B** in this case.
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- **Normalization (`normalize`):** Set to `false` to retain the original scaling of the model weights during the merge.
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- **INT8 Mask (`int8_mask`):** Enabled (`true`) to apply INT8 quantization masking, optimizing the model for efficient inference without significant loss in precision.
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- **Data Type (`dtype`):** Uses `bfloat16` to maintain computational efficiency while ensuring high precision.
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## π Performance Highlights
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- **Creative Text Generation:** Enhanced ability to produce imaginative and diverse content suitable for creative writing, storytelling, and content creation.
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- **Instruction Following:** Improved performance in understanding and executing user instructions, making the model more responsive and accurate in task execution.
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- **Mathematical Reasoning:** Enhanced capability to handle complex computational tasks with high precision, suitable for technical and analytical applications.
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- **Uncensored Technical Expertise:** Provides robust technical knowledge without content restrictions, making it ideal for specialized technical support and information retrieval.
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- **Optimized Inference:** INT8 masking and `bfloat16` data type contribute to efficient computation, enabling faster response times without compromising quality.
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## π― Use Case & Applications
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**ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix** is designed to excel in environments that demand a combination of creative generation, precise instruction following, mathematical reasoning, and technical expertise. Ideal applications include:
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- **Creative Writing Assistance:** Aiding authors and content creators in generating imaginative narratives, dialogues, and descriptive text.
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- **Interactive Storytelling and Role-Playing:** Enhancing dynamic and engaging interactions in role-playing games and interactive storytelling platforms.
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- **Educational Tools and Tutoring Systems:** Providing detailed explanations, answering questions, and assisting in educational content creation with contextual understanding.
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- **Technical Support and Customer Service:** Offering accurate and contextually relevant responses in technical support scenarios, improving user satisfaction.
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- **Content Generation for Marketing:** Creating compelling and diverse marketing copy, social media posts, and promotional material with creative flair.
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- **Mathematical Problem Solving:** Assisting in solving complex mathematical problems and providing step-by-step explanations for educational purposes.
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- **Technical Documentation and Analysis:** Generating detailed technical documents, reports, and analyses with high precision and clarity.
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## π Usage
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To utilize **ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix**, follow the steps below:
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### Installation
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First, install the necessary libraries:
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```bash
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pip install -qU transformers accelerate
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```
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### Example Code
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Below is an example of how to load and use the model for text generation:
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
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import torch
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# Define the model name
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model_name = "ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix"
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# Load the tokenizer
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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# Load the model
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model = AutoModelForCausalLM.from_pretrained(
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model_name,
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torch_dtype=torch.bfloat16,
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device_map="auto"
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)
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# Initialize the pipeline
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text_generator = pipeline(
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"text-generation",
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model=model,
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+
tokenizer=tokenizer,
|
264 |
+
torch_dtype=torch.bfloat16,
|
265 |
+
device_map="auto"
|
266 |
+
)
|
267 |
+
|
268 |
+
# Define the input prompt
|
269 |
+
prompt = "Explain the significance of artificial intelligence in modern healthcare."
|
270 |
+
|
271 |
+
# Generate the output
|
272 |
+
outputs = text_generator(
|
273 |
+
prompt,
|
274 |
+
max_new_tokens=150,
|
275 |
+
do_sample=True,
|
276 |
+
temperature=0.7,
|
277 |
+
top_k=50,
|
278 |
+
top_p=0.95
|
279 |
+
)
|
280 |
+
|
281 |
+
# Print the generated text
|
282 |
+
print(outputs[0]["generated_text"])
|
283 |
+
```
|
284 |
+
|
285 |
+
### Notes
|
286 |
+
|
287 |
+
- **Fine-Tuning:** This merged model may require fine-tuning to optimize performance for specific applications or domains.
|
288 |
+
|
289 |
+
- **Resource Requirements:** Ensure that your environment has sufficient computational resources, especially GPU-enabled hardware, to handle the model efficiently during inference.
|
290 |
+
|
291 |
+
- **Customization:** Users can adjust parameters such as `temperature`, `top_k`, and `top_p` to control the creativity and diversity of the generated text.
|
292 |
+
|
293 |
+
|
294 |
+
## π License
|
295 |
+
|
296 |
+
This model is open-sourced under the **Apache-2.0 License**.
|
297 |
+
|
298 |
+
## π‘ Tags
|
299 |
+
|
300 |
+
- `merge`
|
301 |
+
- `mergekit`
|
302 |
+
- `model_stock`
|
303 |
+
- `Qwen`
|
304 |
+
- `Homer`
|
305 |
+
- `Anvita`
|
306 |
+
- `Nerd`
|
307 |
+
- `ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix`
|
308 |
+
- `bunnycore/Qandora-2.5-7B-Creative`
|
309 |
+
- `allknowingroger/HomerSlerp1-7B`
|
310 |
+
- `sethuiyer/Qwen2.5-7B-Anvita`
|
311 |
+
- `fblgit/cybertron-v4-qw7B-MGS`
|
312 |
+
- `jeffmeloy/Qwen2.5-7B-nerd-uncensored-v1.0`
|
313 |
+
- `newsbang/Homer-v0.5-Qwen2.5-7B`
|
314 |
+
|
315 |
+
---
|
316 |
+
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
|
317 |
+
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_ZeroXClem__Qwen2.5-7B-HomerAnvita-NerdMix)
|
318 |
+
|
319 |
+
| Metric |Value|
|
320 |
+
|-------------------|----:|
|
321 |
+
|Avg. |34.17|
|
322 |
+
|IFEval (0-Shot) |77.08|
|
323 |
+
|BBH (3-Shot) |36.58|
|
324 |
+
|MATH Lvl 5 (4-Shot)|29.53|
|
325 |
+
|GPQA (0-shot) | 9.28|
|
326 |
+
|MuSR (0-shot) |14.41|
|
327 |
+
|MMLU-PRO (5-shot) |38.13|
|
328 |
+
|
329 |
+
|