Instructions to use sagnikM/qwen_qwen_step100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sagnikM/qwen_qwen_step100 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sagnikM/qwen_qwen_step100", device_map="auto") - Notebooks
- Google Colab
- Kaggle
HiLL Qwen2.5-7B checkpoint โ step 100
Converted from the FSDP checkpoint produced by the HiLL Qwen2.5-7B/OpenThoughts run.
Model subfolders
actor: mathematical reasonerposterior: privileged hint generatorprior: question-only hint generator
Load a role with:
from transformers import AutoModelForCausalLM, AutoTokenizer
repo_id = "sagnikM/qwen_qwen_step100"
role = "actor" # actor, posterior, or prior
model = AutoModelForCausalLM.from_pretrained(repo_id, subfolder=role, torch_dtype="auto")
tokenizer = AutoTokenizer.from_pretrained(repo_id, subfolder=role)
Only model, configuration, and tokenizer artifacts are uploaded; optimizer and trainer state remain in the original VERL checkpoint.
Inference Providers NEW
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