code-slerp
code-slerp is a merge of the following models using LazyMergekit:
- microsoft/codebert-base
- EleutherAI/gpt-neo-x-20b
- openai/codex
- bigscience/bloom
- google/jurassic-1-jumbo
- google/t5-v1_1-large
- facebook/bart-large
𧩠Configuration
slices:
- sources:
- model: microsoft/codebert-base
layer_range: [0, 32]
- model: EleutherAI/gpt-neo-x-20b
layer_range: [0, 32]
- model: openai/codex
layer_range: [0, 32]
- model: bigscience/bloom
layer_range: [0, 32]
- model: google/jurassic-1-jumbo
layer_range: [0, 32]
- model: google/t5-v1_1-large
layer_range: [0, 32]
- model: facebook/bart-large
layer_range: [0, 32]
merge_method: slerp
base_model: microsoft/codebert-base
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: bfloat1
π» Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Or4cl3-1/code-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"])
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