# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("ewqr2130/moe_scratch")
model = AutoModelForCausalLM.from_pretrained("ewqr2130/moe_scratch")Quick Links
run_mistral_dpo_moe_from_init_checkpoint.sh run_mistral_dpo_moe_from_init_checkpoint.sh run_mistral_dpo_moe_from_init_checkpoint.sh run_mistral_dpo_moe_from_init_checkpoint.sh run_mistral_dpo_moe_from_init_checkpoint.sh run_mistral_dpo_moe_from_init_checkpoint.sh run_mistral_dpo_moe_from_init_checkpoint.sh run_mistral_dpo_moe_from_init_checkpoint.sh
run_mistral_dpo_moe_from_init_checkpoint.sh run_mistral_dpo_moe_from_init_checkpoint.sh
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ewqr2130/moe_scratch")