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1models:
2 - model: eren23/slerp-test-turdus-beagle
3 parameters:
4 density: [1, 0.7, 0.1] # density gradient
5 weight: 1.0
6 - model: udkai/Turdus
7 parameters:
8 density: 0.5
9 weight: [0, 0.3, 0.7, 1] # weight gradient
10 - model: 222gate/BrurryDog-7b-v0.1
11 parameters:
12 density: 0.33
13 weight:
14 - filter: mlp
15 value: 0.5
16 - value: 0
17merge_method: dare_ties
18base_model: leveldevai/MarcBeagle-7B
19parameters:
20 normalize: true
21 int8_mask: true
22dtype: bfloat16
23embed_slerp: true
24tokenizer_source: union1!pip install -qU transformers accelerate
2
3from transformers import AutoTokenizer
4import transformers
5import torch
6
7model = "222gate/bleagle-7b-v0.1-test"
8messages = [{"role": "user", "content": "What is a large language model?"}]
9
10tokenizer = AutoTokenizer.from_pretrained(model)
11prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
12pipeline = transformers.pipeline(
13 "text-generation",
14 model=model,
15 torch_dtype=torch.float16,
16 device_map="auto",
17)
18
19outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
20print(outputs[0]["generated_text"])| Metric | Value |
|---|---|
| Avg. | 73.89 |
| AI2 Reasoning Challenge (25-Shot) | 72.27 |
| HellaSwag (10-Shot) | 88.24 |
| MMLU (5-Shot) | 64.37 |
| TruthfulQA (0-shot) | 67.83 |
| Winogrande (5-shot) | 85.48 |
| GSM8k (5-shot) | 65.13 |