File size: 1,372 Bytes
1a2e46e
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
---
license: other
base_model: Qwen/Qwen3-Coder-30B-A3B-Instruct
tags:
  - canxp
  - lora
  - peft
  - lora
---

# maplept2-coder

Fine-tuned by **CanXP AI** ([canxp.ai](https://canxp.ai)) from base model
`Qwen/Qwen3-Coder-30B-A3B-Instruct` using LORA.

## Quick start (Python)

```bash
pip install transformers peft torch
```

```python
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel

base = "Qwen/Qwen3-Coder-30B-A3B-Instruct"
adapter = "canxp-ai/maplept2-coder-25082652"

tokenizer = AutoTokenizer.from_pretrained(base, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
    base, torch_dtype="bfloat16", device_map="auto", trust_remote_code=True
)
model = PeftModel.from_pretrained(model, adapter)

prompt = "Hello!"
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
out = model.generate(**inputs, max_new_tokens=200)
print(tokenizer.decode(out[0], skip_special_tokens=True))
```

## CLI download

```bash
pip install -U "huggingface_hub[cli]"
huggingface-cli download canxp-ai/maplept2-coder-25082652 --local-dir ./maplept2-coder
```

## Training details

- Base model: `Qwen/Qwen3-Coder-30B-A3B-Instruct`
- Method: LORA
- Epochs: 2
- Context length: 4096
- Validation split: 0.1

This adapter inherits the upstream license of the base model. See
LICENSE_NOTICE.txt in this repo for details.