初始化项目，由ModelHub XC社区提供模型

Model: ApolloRaines/Llama-3.3-8B-Instruct-128K-Jbliterated
Source: Original Platform

README.md

@@ -0,0 +1,78 @@
+---
+license: llama3.1
+language:
+- en
+- de
+- fr
+- it
+- pt
+- hi
+- es
+- th
+tags:
+- llama
+- llama-3.3
+- jbliterated
+- uncensored
+- text-generation
+- 128k-context
+base_model: shb777/Llama-3.3-8B-Instruct-128K
+pipeline_tag: text-generation
+---
+
+[![Runs with DeepswapLLM](https://img.shields.io/badge/runs%20with-DeepswapLLM-2496ED)](https://github.com/apolloraines/DeepswapLLM)
+
+**Run this model on a GPU too small to hold it** — full precision, no quantization. [DeepswapLLM](https://github.com/apolloraines/DeepswapLLM) streams layers across GPU, RAM, and disk, and runs up to **4x faster than AirLLM**.
+
+# Llama-3.3-8B-Instruct-128K-Jbliterated v1.6
+
+
+## What is Jbliteration?
+
+
+## v1.6 Changes
+
+- Improved multi-phase processing pipeline for cleaner output
+- More precise geometric decomposition of the refusal subspace
+- No fake compliance — model treats all framings of the same topic equally
+- Resistant to refusal reactivation through finetuning
+- 0 genuine refusals on the Heretic 100-prompt benchmark (mlabonne/harmful_behaviors test split)
+
+## Benchmark
+
+Tested against the [Heretic](https://github.com/p-e-w/heretic) 100-prompt refusal benchmark (mlabonne/harmful_behaviors test[:100]):
+
+| Metric | Score |
+|--------|-------|
+| Refusals | 2/100 (both false positives — keyword match on engaged responses) |
+| Genuine refusals | 0/100 |
+
+## Technical Details
+
+- **Layers modified**: 32/32
+- **Base dtype**: bfloat16
+- **Context window**: 128K tokens
+- **Source model**: [shb777/Llama-3.3-8B-Instruct-128K](https://huggingface.co/shb777/Llama-3.3-8B-Instruct-128K)
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model_id = "ApolloRaines/Llama-3.3-8B-Instruct-128K-Jbliterated"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id, dtype=torch.bfloat16, device_map="auto")
+
+messages = [{"role": "user", "content": "Your prompt here"}]
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer(text, return_tensors="pt").to(model.device)
+out = model.generate(**inputs, max_new_tokens=512, temperature=0.7, do_sample=True)
+print(tokenizer.decode(out[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True))
+```
+
+## License
+
+Same as the base model — Llama 3.1 Community License.
+
+Built with Llama.