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varox34/Llama-3-Mistral-v0.2-Instruct-slerp
Llama-3-Mistral-v0.2-Instruct-slerp is a text generation model from varox34. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
Llama-3-Mistral-v0.2-Instruct-slerp is a merge of the following models using LazyMergekit: meta-llama/Meta-Llama-3-8B-Instruct mistralai/Mistral-7B-Instruct-v0.2
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.safetensors14.5 GB · 100%
From the Hugging Face model README
Llama-3-Mistral-v0.2-Instruct-slerp is a merge of the following models using LazyMergekit:
slices:
- sources:
- model: meta-llama/Meta-Llama-3-8B-Instruct
layer_range:
- 0
- 32
- model: mistralai/Mistral-7B-Instruct-v0.2
layer_range:
- 0
- 32
merge_method: slerp
base_model: meta-llama/Meta-Llama-3-8B-Instruct
parameters:
t:
- filter: self_attn
value:
- 0
- 0.5
- 0.3
- 0.7
- 1
- filter: mlp
value:
- 1
- 0.5
- 0.7
- 0.3
- 0
- value: 0.5
dtype: bfloat16
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "varox34/Llama-3-Mistral-v0.2-Instruct-slerp"
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"])