metadata

language:
  - en
datasets:
  - m-newhauser/senator-tweets

Phi-2 Senator Tweets

Phi-2 finetuned on Senator Tweets.

The starting token is [start] and the ending token is [end]

Example:

from transformers import AutoTokenizer, AutoModelForCausalLM

model = AutoModelForCausalLM.from_pretrained("Realluke/phi-2-senator-tweets", torch_dtype="auto", trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained("microsoft/phi-2", trust_remote_code=True)

inputs = tokenizer("[start]", return_tensors="pt", return_attention_mask=False)
outputs = model.generate(**inputs, max_length=200)
text = tokenizer.batch_decode(outputs)[0]

print(text)

Model Details

Model Description

Steps: 750
Finetuning Examples: 1000
GPU: NVIDIA Tesla T4
GPU Hours: 2