---
tags:
- merge
- mergekit
- lazymergekit
- NousResearch/Hermes-3-Llama-3.1-8B
- Replete-AI/Replete-LLM-V2-Llama-3.1-8b
base_model:
- NousResearch/Hermes-3-Llama-3.1-8B
- Replete-AI/Replete-LLM-V2-Llama-3.1-8b
model-index:
- name: Herplete-LLM-Llama-3.1-8b
  results:
  - 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: 46.72
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Etherll/Herplete-LLM-Llama-3.1-8b
      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: 28.95
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Etherll/Herplete-LLM-Llama-3.1-8b
      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: 2.79
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Etherll/Herplete-LLM-Llama-3.1-8b
      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: 4.81
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Etherll/Herplete-LLM-Llama-3.1-8b
      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: 6.68
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Etherll/Herplete-LLM-Llama-3.1-8b
      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: 27.57
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Etherll/Herplete-LLM-Llama-3.1-8b
      name: Open LLM Leaderboard
---

# Herplete-LLM-Llama-3.1-8b


Herplete-LLM-Llama-3.1-8b is a continuous finetuned model from Replete-AI/Replete-LLM-V2-Llama-3.1-8b using Lora extracted from Hermes-3-Llama-3.1-8B.

You can find the continuous finetuning method here:

https://docs.google.com/document/d/1OjbjU5AOz4Ftn9xHQrX3oFQGhQ6RDUuXQipnQ9gn6tU/edit?usp=sharing

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Etherll/Herplete-LLM-Llama-3.1-8b"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Etherll__Herplete-LLM-Llama-3.1-8b)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |19.59|
|IFEval (0-Shot)    |46.72|
|BBH (3-Shot)       |28.95|
|MATH Lvl 5 (4-Shot)| 2.79|
|GPQA (0-shot)      | 4.81|
|MuSR (0-shot)      | 6.68|
|MMLU-PRO (5-shot)  |27.57|