|
--- |
|
datasets: |
|
- heegyu/wizard_vicuna_70k_v2 |
|
license: apache-2.0 |
|
--- |
|
|
|
Hyperparameters |
|
- 3/8 epoch(3rd epoch checkpoing while 8epoch training) |
|
- 1e-4 -> 1e-5 with cosine lr decay |
|
- batch size 128 |
|
- max sequence length 2048 |
|
- AdamW(weigth decay=0.01, b1=0.9, b2=0.99, grad_clip=1.0) |
|
- no warmup |
|
- BF16 |
|
- Base Model: [openlm-research/open_llama_3b_v2](https://huggingface.co/openlm-research/open_llama_3b_v2) |
|
|
|
``` |
|
from transformers import AutoTokenizer, AutoModelForCausalLM |
|
|
|
tokenizer = AutoTokenizer.from_pretrained("heegyu/WizardVicuna-open-llama-3b-v2") |
|
model = AutoModelForCausalLM.from_pretrained("heegyu/WizardVicuna-open-llama-3b-v2") |
|
|
|
inputs = tokenizer(["Human: Hi, nice to meet you!\n\nAssistant: "], return_tensors="pt") |
|
outputs = model.generate(**inputs, max_new_tokens=16) |
|
print(tokenizer.batch_decode(outputs, skip_special_tokens=False)) |
|
``` |
|
|
|
output: `['Human: Hi, nice to meet you!\n\nAssistant: Hello. Great to meet you too. Well, how can I assist you today?<|endoftext|>']` |
