Instructions to use OnAnOrange/llada-8b-pubmed-lp-notopo-2hop-r64-ep5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use OnAnOrange/llada-8b-pubmed-lp-notopo-2hop-r64-ep5 with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Configuration Parsing Warning:In adapter_config.json: "peft.task_type" must be a string
llada-8b-pubmed-lp-notopo-2hop-r64-ep5
This repository contains a LoRA adapter checkpoint for LLaDA-8B trained for graph link prediction on pubmed with no-topology 2hop graph context.
Model Details
- Base model:
GSAI-ML/LLaDA-8B-Instruct - Adapter type: LoRA / PEFT adapter
- Dataset:
pubmed - Task:
lp(link prediction) - Graph context:
notopo(no-topology) - Hop setting:
2hop - LoRA rank:
r64 - Training epochs:
ep5 - Selected checkpoint:
checkpoint-final
Files
adapter_model.safetensors: LoRA adapter weightsadapter_config.json: PEFT adapter configurationtokenizer.json,tokenizer_config.json,special_tokens_map.json: tokenizer fileschat_template.jinja: chat template used with the checkpointtraining_args.bin: serialized training argumentsmetadata.json: structured provenance metadataSOURCE_RUN.txt: source training run provenance
Usage
from transformers import AutoModel, AutoTokenizer
from peft import PeftModel
base_model_id = "GSAI-ML/LLaDA-8B-Instruct"
adapter_id = "OnAnOrange/llada-8b-pubmed-lp-notopo-2hop-r64-ep5"
tokenizer = AutoTokenizer.from_pretrained(adapter_id, trust_remote_code=True)
base_model = AutoModel.from_pretrained(
base_model_id,
trust_remote_code=True,
torch_dtype="auto",
)
model = PeftModel.from_pretrained(base_model, adapter_id)
The exact inference wrapper depends on the DLM-Graph/LLaDA evaluation pipeline. This repository publishes the trained adapter and provenance files, not a standalone merged full model.
Provenance
Original local training run:
tmdlm-llada-8b-pubmed-lp-2hop-notopo-r64-ep5-pubmed_lp_llaga_notopo_20260523_0829_8gpu_5ep
The uploaded checkpoint is checkpoint-final from that run. See
metadata.json and SOURCE_RUN.txt for the exact local source path.
Limitations
This checkpoint is specialized for DLM-Graph experiments. It is not intended as a general-purpose instruction model. Users should evaluate it within the same graph prompting and decoding setup used by the DLM-Graph experiments.
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Base model
GSAI-ML/LLaDA-8B-Instruct