2.0 KiB
library_name, pipeline_tag, base_model, license, tags
| library_name | pipeline_tag | base_model | license | tags | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| transformers | text-generation | Qwen/Qwen2.5-1.5B-Instruct | apache-2.0 |
|
C
Summary
This model is the C BrainAlign stage-2 LoRA checkpoint (best_by_retrieval) merged into the full base model Qwen/Qwen2.5-1.5B-Instruct.
The folder is saved in standard Hugging Face format so it can be uploaded directly for Open LLM Leaderboard v2 evaluation.
Model Details
- Repository:
stech2333/brainalign-qwen2.5-1.5b-C - Architecture:
Qwen2ForCausalLM - Base model:
Qwen/Qwen2.5-1.5B-Instruct - Format: merged full-weights Hugging Face Transformers checkpoint
- Precision for leaderboard submission:
bfloat16
Intended Use
This model is intended for research and evaluation of the BrainAlign stage-2 fine-tuning branch C. It is suitable for standard Hugging Face transformers loading and for leaderboard-style offline evaluation where a full model repository is required instead of a standalone LoRA adapter.
Export Metadata
- Export time:
2026-05-14T19:55:09 - Model kind:
merged_lora - Base model:
Qwen/Qwen2.5-1.5B-Instruct - Checkpoint choice:
best_by_retrieval - Projector branch:
C - Stage-1 head:
mean5_pca1024_contrastive_seed42
License
This merged checkpoint is distributed under apache-2.0, following the declared license metadata in this repository. Please also review the upstream base model card for any additional usage notes from Qwen/Qwen2.5-1.5B-Instruct.
Limitations
This repository documents packaging and export details for evaluation. It does not claim additional safety alignment or benchmark superiority beyond the fine-tuning performed in the BrainAlign project. Downstream behavior should be validated on the target tasks before real use.
Loading
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("C")
tokenizer = AutoTokenizer.from_pretrained("C")