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sequelbox_-_Llama3.1-8B-PlumCode-gguf
RichardErkhov/sequelbox_-_Llama3.1-8B-PlumCode-gguf
sequelbox_-_Llama3.1-8B-PlumCode-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
- Oct 30, 2024
- Updated
- Oct 31, 2024
- SHA
- b80cc229
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
Llama3.1-8B-PlumCode - GGUF
- Model creator: https://huggingface.co/sequelbox/
- Original model: https://huggingface.co/sequelbox/Llama3.1-8B-PlumCode/
| Name | Quant method | Size |
|---|---|---|
| Llama3.1-8B-PlumCode.Q2_K.gguf | Q2_K | 2.96GB |
| Llama3.1-8B-PlumCode.Q3_K_S.gguf | Q3_K_S | 3.41GB |
| Llama3.1-8B-PlumCode.Q3_K.gguf | Q3_K | 3.12GB |
| Llama3.1-8B-PlumCode.Q3_K_M.gguf | Q3_K_M | 3.26GB |
| Llama3.1-8B-PlumCode.Q3_K_L.gguf | Q3_K_L | 4.03GB |
| Llama3.1-8B-PlumCode.IQ4_XS.gguf | IQ4_XS | 4.18GB |
| Llama3.1-8B-PlumCode.Q4_0.gguf | Q4_0 | 4.34GB |
| Llama3.1-8B-PlumCode.IQ4_NL.gguf | IQ4_NL | 4.38GB |
| Llama3.1-8B-PlumCode.Q4_K_S.gguf | Q4_K_S | 4.37GB |
| Llama3.1-8B-PlumCode.Q4_K.gguf | Q4_K | 4.58GB |
| Llama3.1-8B-PlumCode.Q4_K_M.gguf | Q4_K_M | 4.58GB |
| Llama3.1-8B-PlumCode.Q4_1.gguf | Q4_1 | 4.78GB |
| Llama3.1-8B-PlumCode.Q5_0.gguf | Q5_0 | 5.21GB |
| Llama3.1-8B-PlumCode.Q5_K_S.gguf | Q5_K_S | 5.21GB |
| Llama3.1-8B-PlumCode.Q5_K.gguf | Q5_K | 5.34GB |
| Llama3.1-8B-PlumCode.Q5_K_M.gguf | Q5_K_M | 5.34GB |
| Llama3.1-8B-PlumCode.Q5_1.gguf | Q5_1 | 5.65GB |
| Llama3.1-8B-PlumCode.Q6_K.gguf | Q6_K | 6.14GB |
| Llama3.1-8B-PlumCode.Q8_0.gguf | Q8_0 | 7.95GB |
Original model description:
library_name: transformers tags:
- mergekit
- merge
- shining-valiant
- shining-valiant-2
- enigma
- plum
- plumcode
- code
- valiant
- valiant-labs
- llama
- llama-3.1
- llama-3.1-instruct
- llama-3.1-instruct-8b
- llama-3
- llama-3-instruct
- llama-3-instruct-8b
- 8b
- code
- code-instruct
- python
- science
- physics
- biology
- chemistry
- compsci
- computer-science
- engineering
- technical
- conversational
- chat
- instruct base_model:
- meta-llama/Llama-3.1-8B-Instruct
- ValiantLabs/Llama3.1-8B-Enigma
- ValiantLabs/Llama3.1-8B-ShiningValiant2 model-index:
- name: Llama3.1-8B-PlumCode
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: Winogrande (5-Shot)
type: Winogrande
args:
num_few_shot: 5
metrics:
- type: acc value: 73.16 name: acc
- 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: 20.45 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode 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: 8.5 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode 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: 2.42 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode 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: 3.47 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode 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: 8.97 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode 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: 14.84 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Winogrande (5-Shot)
type: Winogrande
args:
num_few_shot: 5
metrics:
PlumCode
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the della merge method using meta-llama/Llama-3.1-8B-Instruct as a base.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
merge_method: della
dtype: bfloat16
parameters:
normalize: true
models:
- model: ValiantLabs/Llama3.1-8B-ShiningValiant2
parameters:
density: 0.5
weight: 0.3
- model: ValiantLabs/Llama3.1-8B-Enigma
parameters:
density: 0.5
weight: 0.25
base_model: meta-llama/Llama-3.1-8B-Instruct
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 9.77 |
| IFEval (0-Shot) | 20.45 |
| BBH (3-Shot) | 8.50 |
| MATH Lvl 5 (4-Shot) | 2.42 |
| GPQA (0-shot) | 3.47 |
| MuSR (0-shot) | 8.97 |
| MMLU-PRO (5-shot) | 14.84 |
- Created
- Oct 30, 2024
- Updated
- Oct 31, 2024