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1models:
2 - model: saishf/West-Hermes-7B
3 # no parameters necessary for base model
4 - model: SanjiWatsuki/Silicon-Maid-7B
5 parameters:
6 weight: 0.4
7 density: 0.8
8 - model: chargoddard/loyal-piano-m7-cdpo
9 parameters:
10 weight: 0.3
11 density: 0.8
12 - model: jsfs11/RandomMergeNoNormWEIGHTED-7B-DARETIES
13 parameters:
14 weight: 0.25
15 density: 0.45
16 - model: NeverSleep/Noromaid-7b-v0.2
17 parameters:
18 weight: 0.25
19 density: 0.4
20 - model: athirdpath/NSFW_DPO_vmgb-7b
21 parameters:
22 weight: 0.2
23 density: 0.4
24merge_method: dare_ties
25base_model: saishf/West-Hermes-7B
26parameters:
27 int8_mask: true
28dtype: bfloat161!pip install -qU transformers accelerate
2
3from transformers import AutoTokenizer
4import transformers
5import torch
6
7model = "jsfs11/HighdensityRPMerge-7B"
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"])