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---
base_model:
- NousResearch/Hermes-3-Llama-3.1-8B
- Replete-AI/Replete-LLM-V2-Llama-3.1-8b
tags:
- merge
- mergekit
- lazymergekit
- NousResearch/Hermes-3-Llama-3.1-8B
- Replete-AI/Replete-LLM-V2-Llama-3.1-8b
---
# Replete-LLM-V3-Llama-3.1-8b
Replete-LLM-V3-Llama-3.1-8b is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [Etherll/Replete-LLM-V3-Llama-3.1-8b-merged](https://huggingface.co/Etherll/Replete-LLM-V3-Llama-3.1-8b-merged)
* [Replete-AI/Replete-LLM-V2-Llama-3.1-8b](https://huggingface.co/Replete-AI/Replete-LLM-V2-Llama-3.1-8b)
## 🧩 Configuration
```yaml
models:
- model: NousResearch/Hermes-3-Llama-3.1-8B
parameters:
weight: 1
- model: Replete-AI/Replete-LLM-V2-Llama-3.1-8b
parameters:
weight: 1
merge_method: ties
base_model: rombodawg/Meta-Llama-3.1-8B-reuploaded
parameters:
normalize: true
int8_mask: true
dtype: bfloat16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Etherll/Replete-LLM-V3-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"])
``` |