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models:
- model: rwitz2/go-bruins-v2.1.1
# no parameters necessary for base model
- model: janai-hq/trinity-v1 # psmathur/orca_mini_v3_13b
parameters:
density: [1, 0.7, 0.1] # density gradient
weight: 1.0
- model: ignos/LeoScorpius-GreenNode-Alpaca-7B-v1
parameters:
density: 0.5
weight: [0, 0.3, 0.7, 1] # weight gradient
- model: mncai/mistral-7b-dpo-v6
parameters:
density: 0.33
weight:
- filter: mlp
value: 0.5
- value: 0
merge_method: ties
base_model: rwitz2/go-bruins-v2.1.1
parameters:
normalize: true
int8_mask: true
dtype: float161from transformers import AutoConfig, AutoModel, AutoTokenizer
2import transformers
3import torch
4hf_model = 'mncai/mistral-7b-dpo-merge-v1'
5message = "<|user|>\n두 개의 구가 있는데 각각 지름이 1, 2일때 구의 부피는 몇배 차이가 나지? 설명도 같이 해줘.\n<|assistant|>\n"
6
7sequences = pipeline(
8 message,
9 do_sample=True,
10 top_k=10,
11 num_return_sequences=1,
12 eos_token_id=tokenizer.eos_token_id,
13 max_length=2048,
14)
15for seq in sequences:
16 print(f"Result: {seq['generated_text']}")