metadata
widget:
- text: Who is Alan Turing?
example_title: Person
- text: What is Aurora Borealis?
example_title: Question
- text: Solve this, 2x+8=18
example_title: Math
license: apache-2.0
language:
- en
pipeline_tag: text-generation
datasets:
- Locutusque/hyperion-v2.0
This model is frankenmerge from gemma-2b-it. Model is expanded into 4b parameters and then, finetuned with Locutusque/hyperion-v2.0 (50k)
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "frankenmerger/gemoy-4b-instruct-scientific-v2"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])