Edit model card

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
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|>']

Downloads last month
5,138
Safetensors
Model size
3.43B params
Tensor type
F32
Β·
FP16
Β·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for heegyu/WizardVicuna-open-llama-3b-v2

Adapters
2 models
Quantizations
1 model

Dataset used to train heegyu/WizardVicuna-open-llama-3b-v2

Spaces using heegyu/WizardVicuna-open-llama-3b-v2 21