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/generation_manifest.json from tianzl66/Qwen3-8B-Magicoder-50K-LoRA-E1-Seed44: direct link, hf CLI and curl.
- Browser
- Download file 1.51 kB
-
https://huggingface.co/tianzl66/Qwen3-8B-Magicoder-50K-LoRA-E1-Seed44/resolve/main/evaluation/generation_manifest.json
- Command line
-
hf download hf://tianzl66/Qwen3-8B-Magicoder-50K-LoRA-E1-Seed44/evaluation/generation_manifest.json
-
curl -L -o generation_manifest.json https://huggingface.co/tianzl66/Qwen3-8B-Magicoder-50K-LoRA-E1-Seed44/resolve/main/evaluation/generation_manifest.json
1.51 kB
| { | |
| "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 | |
| } | |
| } | |