Gemma_Writer-9b is a merge of the following models using
LazyMergekit:
1models:
2 - model: IlyaGusev/gemma-2-9b-it-abliterated
3 # No parameters necessary for base model
4 - model: nbeerbower/gemma2-gutenberg-9B
5 parameters:
6 density: 0.6
7 weight: 0.4
8 - model: UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3
9 parameters:
10 density: 0.53
11 weight: 0.3
12 - model: princeton-nlp/gemma-2-9b-it-SimPO
13 parameters:
14 density: 0.6
15 weight: 0.3
16merge_method: dare_ties
17base_model: IlyaGusev/gemma-2-9b-it-abliterated
18parameters:
19 int8_mask: true
20dtype: bfloat16
1!pip install -qU transformers accelerate
2
3from transformers import AutoTokenizer
4import transformers
5import torch
6
7model = "StoneLabs/Gemma_Writer-9b"
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"])
