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AbacusResearch_-_haLLawa4-7b-gguf
RichardErkhov/AbacusResearch_-_haLLawa4-7b-gguf
AbacusResearch_-_haLLawa4-7b-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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At a glance
- Access
- Public
- Created
- Sep 22, 2024
- Updated
- Sep 22, 2024
- SHA
- 06643695
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
haLLawa4-7b - GGUF
- Model creator: https://huggingface.co/AbacusResearch/
- Original model: https://huggingface.co/AbacusResearch/haLLawa4-7b/
| Name | Quant method | Size |
|---|---|---|
| haLLawa4-7b.Q2_K.gguf | Q2_K | 2.53GB |
| haLLawa4-7b.IQ3_XS.gguf | IQ3_XS | 2.81GB |
| haLLawa4-7b.IQ3_S.gguf | IQ3_S | 2.96GB |
| haLLawa4-7b.Q3_K_S.gguf | Q3_K_S | 2.95GB |
| haLLawa4-7b.IQ3_M.gguf | IQ3_M | 3.06GB |
| haLLawa4-7b.Q3_K.gguf | Q3_K | 3.28GB |
| haLLawa4-7b.Q3_K_M.gguf | Q3_K_M | 3.28GB |
| haLLawa4-7b.Q3_K_L.gguf | Q3_K_L | 3.56GB |
| haLLawa4-7b.IQ4_XS.gguf | IQ4_XS | 3.67GB |
| haLLawa4-7b.Q4_0.gguf | Q4_0 | 3.83GB |
| haLLawa4-7b.IQ4_NL.gguf | IQ4_NL | 3.87GB |
| haLLawa4-7b.Q4_K_S.gguf | Q4_K_S | 3.86GB |
| haLLawa4-7b.Q4_K.gguf | Q4_K | 4.07GB |
| haLLawa4-7b.Q4_K_M.gguf | Q4_K_M | 4.07GB |
| haLLawa4-7b.Q4_1.gguf | Q4_1 | 4.24GB |
| haLLawa4-7b.Q5_0.gguf | Q5_0 | 4.65GB |
| haLLawa4-7b.Q5_K_S.gguf | Q5_K_S | 4.65GB |
| haLLawa4-7b.Q5_K.gguf | Q5_K | 4.78GB |
| haLLawa4-7b.Q5_K_M.gguf | Q5_K_M | 4.78GB |
| haLLawa4-7b.Q5_1.gguf | Q5_1 | 5.07GB |
| haLLawa4-7b.Q6_K.gguf | Q6_K | 5.53GB |
| haLLawa4-7b.Q8_0.gguf | Q8_0 | 7.17GB |
Original model description:
license: apache-2.0 tags:
- merge
- mergekit
- lazymergekit
- mlabonne/Monarch-7B
- paulml/OGNO-7B
- AbacusResearch/haLLAwa3 model-index:
- name: haLLawa4-7b
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: AI2 Reasoning Challenge (25-Shot)
type: ai2_arc
config: ARC-Challenge
split: test
args:
num_few_shot: 25
metrics:
- type: acc_norm value: 71.5 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AbacusResearch/haLLawa4-7b name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: HellaSwag (10-Shot)
type: hellaswag
split: validation
args:
num_few_shot: 10
metrics:
- type: acc_norm value: 88.36 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AbacusResearch/haLLawa4-7b name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU (5-Shot)
type: cais/mmlu
config: all
split: test
args:
num_few_shot: 5
metrics:
- type: acc value: 64.49 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AbacusResearch/haLLawa4-7b name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: TruthfulQA (0-shot)
type: truthful_qa
config: multiple_choice
split: validation
args:
num_few_shot: 0
metrics:
- type: mc2 value: 74.27 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AbacusResearch/haLLawa4-7b name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Winogrande (5-shot)
type: winogrande
config: winogrande_xl
split: validation
args:
num_few_shot: 5
metrics:
- type: acc value: 82.4 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AbacusResearch/haLLawa4-7b name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GSM8k (5-shot)
type: gsm8k
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc value: 70.51 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AbacusResearch/haLLawa4-7b name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: AI2 Reasoning Challenge (25-Shot)
type: ai2_arc
config: ARC-Challenge
split: test
args:
num_few_shot: 25
metrics:
haLLawa4-7b
haLLawa4-7b is a merge of the following models using mergekit:
🧩 Configuration
```yaml models:
- model: eren23/ogno-monarch-jaskier-merge-7b
No parameters necessary for base model
- model: mlabonne/Monarch-7B #Emphasize the beginning of Vicuna format models parameters: weight: 0.5 density: 0.59
- model: paulml/OGNO-7B parameters: weight: 0.2 density: 0.55
Vicuna format
- model: AbacusResearch/haLLAwa3 parameters: weight: 0.3 density: 0.55
merge_method: dare_ties base_model: eren23/ogno-monarch-jaskier-merge-7b parameters: int8_mask: true dtype: bfloat16 random_seed: 0 ```
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 75.25 |
| AI2 Reasoning Challenge (25-Shot) | 71.50 |
| HellaSwag (10-Shot) | 88.36 |
| MMLU (5-Shot) | 64.49 |
| TruthfulQA (0-shot) | 74.27 |
| Winogrande (5-shot) | 82.40 |
| GSM8k (5-shot) | 70.51 |
- Created
- Sep 22, 2024
- Updated
- Sep 22, 2024