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minotaur-llama2-13b-qlora
QuixiAI/minotaur-llama2-13b-qlora
minotaur-llama2-13b-qlora is a machine learning model from QuixiAI. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft.
The following bitsandbytes quantization config was used during training: - loadin8bit: False - loadin4bit: True - llmint8threshold: 6.0 - llmint8skipmodules: None - llmint8enablefp32cpuoffload: False - llmint8hasfp16w…
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At a glance
- Library
- peft
- Access
- Public
- Created
- Aug 3, 2023
- Updated
- Mar 4, 2024
- SHA
- b8cae9b8
Base models
Model card
From the Hugging Face model README
Training procedure
The following bitsandbytes quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: float32
The following bitsandbytes quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: float32
The following bitsandbytes quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: float32
The following bitsandbytes quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: float32
Framework versions
-
PEFT 0.5.0.dev0
-
PEFT 0.5.0.dev0
-
PEFT 0.5.0.dev0
-
PEFT 0.5.0.dev0
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 49.54 |
| ARC (25-shot) | 60.07 |
| HellaSwag (10-shot) | 82.42 |
| MMLU (5-shot) | 55.87 |
| TruthfulQA (0-shot) | 45.57 |
| Winogrande (5-shot) | 76.24 |
| GSM8K (5-shot) | 12.05 |
| DROP (3-shot) | 14.53 |
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 55.37 |
| AI2 Reasoning Challenge (25-Shot) | 60.07 |
| HellaSwag (10-Shot) | 82.42 |
| MMLU (5-Shot) | 55.87 |
| TruthfulQA (0-shot) | 45.57 |
| Winogrande (5-shot) | 76.24 |
| GSM8k (5-shot) | 12.05 |
- Library
- peft
- Created
- Aug 3, 2023
- Updated
- Mar 4, 2024