metadata
tags:
- merge
- OpenPipe/mistral-ft-optimized-1227
- Nexusflow/Starling-LM-7B-beta
base_model:
- OpenPipe/mistral-ft-optimized-1227
- Nexusflow/Starling-LM-7B-beta
license: apache-2.0
M-LChat-7b
M-LChat-7b is a merge of the following models using:
Configuration
slices:
- sources:
- model: OpenPipe/mistral-ft-optimized-1227
layer_range: [0, 32]
- model: Nexusflow/Starling-LM-7B-beta
layer_range: [0, 32]
merge_method: slerp
base_model: OpenPipe/mistral-ft-optimized-1227
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
Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Artples/M-LChat-7b"
messages = [{GPT4 Correct User: What can i do if a lama is in my porch?<|end_of_turn|>GPT4 Correct Assistant:}]
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"])
How?
Usage of LazyMergekit on a T4.