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teknium/Puffin-Phi-v2
Puffin-Phi-v2 is a text generation model from teknium. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as other.
This is my first fine-tune of Puffin that seems to be working fairly reliably!
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From the Hugging Face model README
This is my first fine-tune of Puffin that seems to be working fairly reliably!

This model was trained on the Puffin Dataset, made by LDJ, using a slightly modified version of the dataset that removed >2000 token entries, so there would be no early cutoffs during training phi, since it's context is 2k.
Let me know!
Phi does not support device_map "auto", and does not seem to want to inference in fp16, so use bf16.
Here is working code to inference, though it can be improved:
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
sysprompt = "The assistant gives helpful, detailed, and polite answers to the user's questions.\n"
model = AutoModelForCausalLM.from_pretrained("teknium/Puffin-Phi-v2", trust_remote_code=True, torch_dtype=torch.bfloat16).to("cuda")
tokenizer = AutoTokenizer.from_pretrained("teknium/Puffin-Phi-v2", trust_remote_code=True, torch_dtype=torch.bfloat16)
inputs = tokenizer(f"{sysprompt}USER: Write a negative review for the website Twitter.\nASSISTANT:", return_tensors="pt", return_attention_mask=False)
outputs = model.generate(**inputs, max_length=128, do_sample=True, temperature=0.2, top_p=0.9, use_cache=True, repetition_penalty=1.2, eos_token_id=tokenizer.eos_token_id)
text = tokenizer.batch_decode(outputs)[0]
print(text)
The prompt format is ShareGPT/Vicuna, so it uses the sysprompt (defualt in sysprompt variable) then is prompted like so:
USER: <prompt>
ASSISTANT:
Trained with Axolotl. View the wandb runs for all my puffin runs (this is puffin-phi-4 on wandb): https://wandb.ai/teknium1/puffin-phi/runs/puffin-phi-4
TODO