netcat420/MFANN
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How to use netcat420/MFANN3bv0.6 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="netcat420/MFANN3bv0.6") # Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("netcat420/MFANN3bv0.6")
model = AutoModelForCausalLM.from_pretrained("netcat420/MFANN3bv0.6", device_map="auto")MFANN 3b version 0.6
fine-tuned on the MFANN dataset as it stands on 5/2/2024 as it is an ever changing and expaning dataset.
benchmark results for this 3b model:
64.34 <-- Average 62.63 <-- Arc 77.1 <-- HellaSwag 58.43 <-- MMLU 51.71 <-- TruthfulQA 74.66 <-- Winogrande 61.49 <-- GSM8K
currently the worlds best 2.78B parameter model!!!!!!!!!!! as of 5/2/2024