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QuantFactory/Halu-8B-Llama3-Blackroot-GGUF
Halu-8B-Llama3-Blackroot-GGUF is a text generation model from QuantFactory. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as llama3.
This is quantized version of Hastagaras/Halu-8B-Llama3-Blackroot created using llama.cpp
Downloads · 30 days
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From the Hugging Face model README
This is quantized version of Hastagaras/Halu-8B-Llama3-Blackroot created using llama.cpp
VERY IMPORTANT: This model has not been extensively tested or evaluated, and its performance characteristics are currently unknown. It may generate harmful, biased, or inappropriate content. Please exercise caution and use it at your own risk and discretion.
I just tried saishf's merged model, and it's great. So I decided to try a similar merge method with Blackroot's LoRA that I had found earlier.
I don't know what to say about this model... this model is very strange...Maybe because Blackroot's amazing Loras used human data and not synthetic data, hence the model turned out to be very human-like...even the actions or narrations.
WARNING: This model is very unsafe in certain parts...especially in RP.
IMATRIX GGUF IS HERE made available by Lewdiculous
STATIC GGUF IS HERE made avaible by mradermacher
<div align="left"> <img src="https://huggingface.co/Hastagaras/Halu-8B-Llama3-Blackroot/resolve/main/Halu (1).png" width="500"/> </div>This model was merged using the Model Stock merge method using Hastagaras/Halu-8B-Llama3-v0.3 as a base.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
models:
- model: Hastagaras/Halu-8B-Llama3-v0.3+Blackroot/Llama-3-LongStory-LORA
- model: Hastagaras/Halu-8B-Llama3-v0.3+Blackroot/Llama-3-8B-Abomination-LORA
merge_method: model_stock
base_model: Hastagaras/Halu-8B-Llama3-v0.3
dtype: bfloat16
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 69.78 |
| AI2 Reasoning Challenge (25-Shot) | 63.82 |
| HellaSwag (10-Shot) | 84.55 |
| MMLU (5-Shot) | 67.04 |
| TruthfulQA (0-shot) | 53.28 |
| Winogrande (5-shot) | 79.48 |
| GSM8k (5-shot) | 70.51 |