初始化项目，由ModelHub XC社区提供模型

Model: frankmorales2020/deepseek-governed-no-amnesia
Source: Original Platform

README.md

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+---
+license: mit
+base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
+tags:
+  - deepseek
+  - experimental
+  - research
+library_name: transformers
+pipeline_tag: text-generation
+---
+
+CODE: https://github.com/frank-morales2020/AST/blob/main/DEEPSEEK_PRIME_ANCHORE_LLM.ipynb
+
+
+# deepseek-governed-no-amnesia
+
+An experimental repository pairing **DeepSeek-R1-Distill-Qwen-7B** with a
+"Prime-Anchored Spectral Governor" artifact. This card describes exactly what
+the repository contains and what the accompanying run did and did not do.
+
+## What this repository is
+
+- The model weights are **identical to the base model**,
+  [`deepseek-ai/DeepSeek-R1-Distill-Qwen-7B`](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B).
+  The governor did not modify them.
+- Attached is `governor_state.pt`, which records the governor configuration
+  (anchor primes, threshold, cached anchor rows, gate statistics, and a
+  SHA-256 signature of the prime-indexed embedding rows).
+- `VERIFICATION.txt` records the run details.
+
+## What the governor does (and doesn't)
+
+The governor evaluates a gate on each training step and pins six
+prime-indexed embedding rows (`[2, 3, 5, 7, 11, 13]`) to their original
+values. In the run that produced this repository, the optimizer step was a
+**no-op** (`STEP_GATED_NO_MUTATION`), so the model was not trained or
+fine-tuned.
+
+As a result:
+
+- The prime-indexed rows are unchanged (anchor signature matches).
+- The full model is byte-for-byte the base model.
+- **This run does not demonstrate** training, fine-tuning, or that any form
+  of catastrophic forgetting was prevented, because the model was not
+  modified. The repository name reflects the project's intent, not a
+  measured property of this checkpoint.
+
+## Intended use
+
+Research and experimentation with the governor tooling. For general use,
+loading the base model directly is equivalent and avoids downloading a
+duplicate copy of the weights.
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+REPO_ID = "frankmorales2020/deepseek-governed-no-amnesia"
+
+tokenizer = AutoTokenizer.from_pretrained(REPO_ID, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(
+    REPO_ID, torch_dtype=torch.float16, device_map="auto", trust_remote_code=True
+)
+model.eval()
+
+prompt = "Explain why prime numbers are important in cryptography."
+text = tokenizer.apply_chat_template(
+    [{"role": "user", "content": prompt}],
+    tokenize=False, add_generation_prompt=True,
+)
+enc = tokenizer(text, return_tensors="pt").to(model.device)
+
+out = model.generate(
+    **enc,
+    max_new_tokens=512,
+    do_sample=True,
+    temperature=0.7,
+    top_p=0.9,
+    repetition_penalty=1.3,
+    no_repeat_ngram_size=3,
+    pad_token_id=tokenizer.eos_token_id,
+)
+print(tokenizer.decode(out[0][enc["input_ids"].shape[1]:], skip_special_tokens=True))
+```
+
+> This is a DeepSeek R1 distill (reasoning) model. Feed prompts through the
+> chat template, and expect a `<think> ... </think>` reasoning trace before
+> the final answer. To keep only the final answer, split the output on
+> `</think>`.
+
+## Inspecting the governor artifact
+
+```python
+from huggingface_hub import hf_hub_download
+import torch
+
+state = torch.load(
+    hf_hub_download(REPO_ID, "governor_state.pt"),
+    map_location="cpu", weights_only=False,
+)
+print(state["primes"], state["LAMBDA_12"], state["anchor_signature"], state["stats"])
+```
+
+## License
+
+Released under the MIT license, inherited from the base model.
+
+## Acknowledgements
+
+Base model: DeepSeek-R1-Distill-Qwen-7B by DeepSeek-AI.