Text Generation
PEFT
Safetensors
lora
spectral-surgery
training-seed-replication
b300
code
seed-44
conversational
Instructions to use tianzl66/Qwen3-8B-Magicoder-50K-LoRA-E1-Seed44 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tianzl66/Qwen3-8B-Magicoder-50K-LoRA-E1-Seed44 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-8B") model = PeftModel.from_pretrained(base_model, "tianzl66/Qwen3-8B-Magicoder-50K-LoRA-E1-Seed44") - Notebooks
- Google Colab
- Kaggle
Download evaluation/benchmark_provenance.json from tianzl66/Qwen3-8B-Magicoder-50K-LoRA-E1-Seed44: direct link, hf CLI and curl.
- Browser
- Download file 470 Bytes
-
https://huggingface.co/tianzl66/Qwen3-8B-Magicoder-50K-LoRA-E1-Seed44/resolve/main/evaluation/benchmark_provenance.json
- Command line
-
hf download hf://tianzl66/Qwen3-8B-Magicoder-50K-LoRA-E1-Seed44/evaluation/benchmark_provenance.json
-
curl -L -o benchmark_provenance.json https://huggingface.co/tianzl66/Qwen3-8B-Magicoder-50K-LoRA-E1-Seed44/resolve/main/evaluation/benchmark_provenance.json
470 Bytes
| { | |
| "filename": "humaneval-test.parquet", | |
| "sha256": "3bea46a554c67c5d2915e2db7d97d7733f09140e7a1776428c1b20b5ae5d124b", | |
| "task": "magicoder", | |
| "evaluation_spec": { | |
| "benchmark": "HumanEval", | |
| "dataset": "<LOCAL_PATH>/humaneval-test.parquet", | |
| "samples": 164, | |
| "primary_metric": "pass@1", | |
| "max_new_tokens": 512 | |
| }, | |
| "provenance_note": "GSM8K/IFEval local inputs were reconstructed from historical scored outputs; HumanEval is local test parquet." | |
| } | |