初始化项目，由ModelHub XC社区提供模型

Model: heegyu/WizardVicuna-open-llama-3b-v2
Source: Original Platform

README.md

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+---
+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|>']`