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from transformers import AutoModelForCausalLM, AutoTokenizer | |
# Model checkpoints | |
models_checkpoints = [ | |
"HuggingFaceTB/SmolLM-135M-Instruct", | |
"HuggingFaceTB/SmolLM-360M", | |
"HuggingFaceTB/SmolLM-360M-Instruct", | |
"HuggingFaceTB/SmolLM-1.7B", | |
"HuggingFaceTB/SmolLM-1.7B-Instruct", | |
"Qwen/Qwen2-1.5B-Instruct", | |
"Qwen/Qwen2-0.5B" | |
] | |
# Dictionary to store models and tokenizers | |
models_and_tokenizers = {} | |
# Loading models and tokenizers | |
for checkpoint in models_checkpoints: | |
model = AutoModelForCausalLM.from_pretrained(checkpoint) | |
tokenizer = AutoTokenizer.from_pretrained(checkpoint) | |
models_and_tokenizers[checkpoint] = (model, tokenizer) | |