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Etherll/Replete-Einstein-7B
Replete-Einstein-7B is a machine learning model from Etherll. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Replete-Einstein-7B is a merge of the following models using LazyMergekit: Etherll/Einstein-v7-Qwen2-7B-merged Replete-AI/Replete-LLM-Qwen2-7b
Downloads · 30 days
6
23% of all-time downloads
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.safetensors15.2 GB · 100%
From the Hugging Face model README
Replete-Einstein-7B is a merge of the following models using LazyMergekit:
models:
- model: Etherll/Einstein-v7-Qwen2-7B-merged
parameters:
weight: 1
- model: Replete-AI/Replete-LLM-Qwen2-7b
parameters:
weight: 1
merge_method: ties
base_model: Qwen/Qwen2-7B
parameters:
normalize: true
int8_mask: true
dtype: bfloat16
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Etherll/Replete-Einstein-7B"
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"])