mmcarpi/carolina-originality-matched
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Checkpoints, training logs, and other artifacts from training the FlexQwen models.
Checkout the FlexQwen repository for more details on the models and training process.
repo_id = "mmcarpi/flexqwen-collection"
config_name = "gold-exponential/best" # dataset-strategy/checkpoint, eg "matched-shift/step_00500"
# Load tokenizer from the root
tokenizer = AutoTokenizer.from_pretrained(repo_id, trust_remote_code=True)
# Load model from the specific configuration subfolder
model = AutoModelForCausalLM.from_pretrained(
repo_id,
subfolder=config_name,
trust_remote_code=True
)