---
library_name: transformers
base_model: openai/gpt-oss-20b
language: [en, ja]
pipeline_tag: text-generation
tags: []
---

# thinker-mini-v1

**Overview**

This is a test model.

**Technical notes**

- Base: `openai/gpt-oss-20b` (bf16)
- Steering: rank-1 delta on Q/K/V across 24 layers (RMSNorm-aware)
- Concept vector: `concept_vec_v15k.pt`, shape [24, 6, 2880], gain=0.5
- Checkpoint: single baked weights (no LoRA/adapters; knowledge ≈ base)
- Data used: neutral_examples=86376, pairs_used=14394
- Source files: `narukijima/thinker` → `T_instruction_pairs_en.jsonl`, `T_instruction_pairs_ja.jsonl`
- Inference: use base tokenizer & chat template

**Quick inference**

```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
M = "narukijima/thinker-mini-v1"
tok = AutoTokenizer.from_pretrained(M, trust_remote_code=True)
mdl = AutoModelForCausalLM.from_pretrained(
    M, torch_dtype=torch.bfloat16, device_map='auto', trust_remote_code=True
)
msgs = [{"role":"user","content":"test"}]
p = tok.apply_chat_template(msgs, tokenize=False, add_generation_prompt=True)
out = mdl.generate(**tok(p, return_tensors='pt').to(mdl.device),
                   max_new_tokens=64, do_sample=True, temperature=0.7)
print(tok.decode(out[0], skip_special_tokens=True))
```