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1base_model: mlabonne/NeuralBeagle14-7B
2gate_mode: cheap_embed
3experts:
4 - source_model: mlabonne/NeuralBeagle14-7B
5 positive_prompts:
6 - "chat"
7 - "assistant"
8 - "explain"
9 - "tell me"
10 - "english"
11 - source_model: timpal0l/Mistral-7B-v0.1-flashback-v2
12 positive_prompts:
13 - "förklara"
14 - "sammanfatta"
15 - "svenska"
16 - source_model: Nexusflow/Starling-LM-7B-beta
17 positive_prompts:
18 - "code"
19 - "programming"
20 - "algorithm"
21 - source_model: AI-Sweden-Models/tyr
22 positive_prompts:
23 - "varför"
24 - "förenkla"
25 - "lagen"1!pip install -qU transformers bitsandbytes accelerate
2
3from transformers import AutoTokenizer
4import transformers
5import torch
6
7model = "FredrikBL/MoEnsterBeagle"
8
9tokenizer = AutoTokenizer.from_pretrained(model)
10pipeline = transformers.pipeline(
11 "text-generation",
12 model=model,
13 model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
14)
15
16messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
17prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
18outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
19print(outputs[0]["generated_text"])