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1models:
2 - model: NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
3 parameters:
4 density: [1, 0.7, 0.1] # density gradient
5 weight: 1.0
6 - model: FPHam/Writing_Partner_Mistral_7B
7 parameters:
8 density: 0.5
9 weight: [0, 0.3, 0.7, 1] # weight gradient
10merge_method: ties
11base_model: NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
12parameters:
13 normalize: true
14 int8_mask: true
15dtype: float161!pip install -qU transformers accelerate
2
3from transformers import AutoTokenizer
4import transformers
5import torch
6
7model = "hvsq/Babylona_v0.1"
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"])