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--- |
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library_name: transformers |
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base_model: openai/gpt-oss-20b |
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language: [en, ja] |
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pipeline_tag: text-generation |
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tags: [] |
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--- |
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# thinker-mini-v1 |
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**Overview** |
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This is a test model. |
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**Technical notes** |
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- Base: `openai/gpt-oss-20b` (bf16) |
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- Steering: rank-1 delta on Q/K/V across 24 layers (RMSNorm-aware) |
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- Concept vector: `concept_vec_v15k.pt`, shape [24, 6, 2880], gain=0.5 |
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- Checkpoint: single baked weights (no LoRA/adapters; knowledge ≈ base) |
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- Data used: neutral_examples=86376, pairs_used=14394 |
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- Source files: `narukijima/thinker` → `T_instruction_pairs_en.jsonl`, `T_instruction_pairs_ja.jsonl` |
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- Inference: use base tokenizer & chat template |
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**Quick inference** |
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```python |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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import torch |
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M = "narukijima/thinker-mini-v1" |
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tok = AutoTokenizer.from_pretrained(M, trust_remote_code=True) |
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mdl = AutoModelForCausalLM.from_pretrained( |
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M, torch_dtype=torch.bfloat16, device_map='auto', trust_remote_code=True |
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) |
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msgs = [{"role":"user","content":"test"}] |
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p = tok.apply_chat_template(msgs, tokenize=False, add_generation_prompt=True) |
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out = mdl.generate(**tok(p, return_tensors='pt').to(mdl.device), |
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max_new_tokens=64, do_sample=True, temperature=0.7) |
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print(tok.decode(out[0], skip_special_tokens=True)) |
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``` |
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