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
File size: 1,508 Bytes
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"status": "generation_complete",
"base_model": "<LOCAL_PATH>/Qwen3-8B",
"variant_manifest": "<LOCAL_PATH>/variant_manifest.json",
"variant_order": [
"magicoder__original_lora",
"magicoder__hns_f0_s0",
"magicoder__hns_f2_s0",
"magicoder__hns_f2_s1",
"magicoder__hns_f2_s2",
"magicoder__hns_f4_s0",
"magicoder__hns_f4_s1",
"magicoder__hns_f4_s2",
"magicoder__hns_f8_s0",
"magicoder__hns_f8_s1",
"magicoder__hns_f8_s2",
"metamath__original_lora",
"metamath__hns_f0_s0",
"metamath__hns_f2_s0",
"metamath__hns_f2_s1",
"metamath__hns_f2_s2",
"metamath__hns_f4_s0",
"metamath__hns_f4_s1",
"metamath__hns_f4_s2",
"metamath__hns_f8_s0",
"metamath__hns_f8_s1",
"metamath__hns_f8_s2",
"tulu__original_lora",
"tulu__hns_f0_s0",
"tulu__hns_f2_s0",
"tulu__hns_f2_s1",
"tulu__hns_f2_s2",
"tulu__hns_f4_s0",
"tulu__hns_f4_s1",
"tulu__hns_f4_s2",
"tulu__hns_f8_s0",
"tulu__hns_f8_s1",
"tulu__hns_f8_s2"
],
"tasks": [
{
"task": "magicoder",
"samples": 164,
"max_tokens": 512
},
{
"task": "metamath",
"samples": 1319,
"max_tokens": 512
},
{
"task": "tulu",
"samples": 541,
"max_tokens": 2048
}
],
"configuration": {
"vllm_batch_invariant": "1",
"gpu_memory_utilization": 0.94,
"max_num_seqs": 1024,
"max_num_batched_tokens": 65536,
"adapter_block_size": 11,
"seed": 42
}
}
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