Mistral 7B Merges
Collection
Merges that may or may not be worth using. All credit goes to Maxime Labonne's course, https://github.com/mlabonne/llm-course, + mergekit
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6 items
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Updated
WildMBXMarconi-SLERP-7B is a merge of the following models using LazyMergekit:
slices:
- sources:
- model: BarryFutureman/WildMarcoroni-Variant1-7B
layer_range: [0, 32]
- model: flemmingmiguel/MBX-7B
layer_range: [0, 32]
merge_method: slerp
base_model: BarryFutureman/WildMarcoroni-Variant1-7B
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: 0.45 # fallback for rest of tensors
dtype: bfloat16
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "jsfs11/WildMBXMarconi-SLERP-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"])
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 75.09 |
AI2 Reasoning Challenge (25-Shot) | 73.29 |
HellaSwag (10-Shot) | 88.49 |
MMLU (5-Shot) | 64.90 |
TruthfulQA (0-shot) | 68.98 |
Winogrande (5-shot) | 83.98 |
GSM8k (5-shot) | 70.89 |