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Model: derprofi2431/Prisma-32B Source: Original Platform
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README.md
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---
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license: apache-2.0
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tags:
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- prisma
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- coding
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- cybersecurity
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- reasoning
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- uncensored
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- agent
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language:
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- en
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- de
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- zh
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library_name: transformers
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pipeline_tag: text-generation
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---
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# Prisma-32B
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**Prisma-32B** is a 32 billion parameter language model optimized for advanced coding, technical reasoning, and cybersecurity workflows. It the first Prisma Model with no security blocking. It is the second release in the **Prisma** series, following [`Prisma-0.6B`](https://huggingface.co/derprofi2431/Prisma-0.6B).
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Prisma-32B is designed to be a capable, direct, and technically rigorous assistant for users who need a model that engages substantively with complex technical material.
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---
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## Model Details
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| Property | Value |
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|---|---|
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| **Parameters** | 32B |
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| **Architecture** | Transformer Decoder |
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| **Context Length** | 32,768 tokens |
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| **Languages** | English, German, Chinese (+ 20 more) |
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| **License** | Apache 2.0 |
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---
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## Intended Use
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Prisma-32B is intended for:
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- **Coding assistance** — full-stack development, debugging, refactoring, code review
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- **Cybersecurity research** — offensive security workflows (red team, CTF, exploit analysis) and defensive workflows (incident response, hardening, secure code review)
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- **Technical writing** — documentation, system specifications, architecture
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- **Research and experimentation** in controlled environments
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---
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## Usage
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained(
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"derprofi2431/Prisma-32B",
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torch_dtype="auto",
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device_map="auto",
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)
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tokenizer = AutoTokenizer.from_pretrained("derprofi2431/Prisma-32B")
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messages = [
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{"role": "user", "content": "Write a port scanner in Python."}
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]
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inputs = tokenizer.apply_chat_template(
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messages, return_tensors="pt", add_generation_prompt=True
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).to(model.device)
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output = model.generate(inputs, max_new_tokens=2048, temperature=0.7)
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print(tokenizer.decode(output[0], skip_special_tokens=True))
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```
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### Recommended Sampling
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| Parameter | Value |
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|---|---|
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| `temperature` | 0.6 – 0.8 |
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| `top_p` | 0.9 |
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| `top_k` | 40 |
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| `repetition_penalty` | 1.05 |
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---
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## Quantized Versions
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GGUF quantizations for local inference via Ollama and llama.cpp will be released as separate repositories.
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---
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## Limitations and Responsible Use
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- The user is fully responsible for the content they generate and how they use it.
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- The model is not aligned for general consumer-facing deployment. For production use, deploy behind an appropriate safety layer (input filtering, output classification, etc.).
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- The model may reflect biases present in large-scale text corpora.
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- Intended for adult, technically competent users in controlled environments.
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By downloading or using this model, you agree to use it lawfully and ethically within your jurisdiction. The author assumes no liability for misuse.
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---
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## Citation
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```bibtex
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@misc{prisma32b2026,
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title = {Prisma-32B},
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author = {Jannik},
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year = {2026},
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url = {https://huggingface.co/derprofi2431/Prisma-32B}
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}
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```
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abliteration_metadata.json
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{
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"source_model": "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
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"technique": "refusal_direction_ablation",
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"method": "advanced",
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"method_config": {
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"n_directions": 4,
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"direction_method": "svd",
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"norm_preserve": true,
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"regularization": 0.3,
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"refinement_passes": 2,
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"project_biases": true,
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"use_chat_template": true,
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"use_whitened_svd": false,
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"true_iterative_refinement": false,
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"winsorize_activations": false,
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"float_layer_interpolation": false,
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"cot_aware": false,
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"use_kl_optimization": false,
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"use_lora_ablation": false,
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"spectral_cascade": false,
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"spectral_bands": 3,
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"spectral_threshold": 0.05
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},
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"references": [
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"Arditi et al., Refusal in Language Models Is Mediated by a Single Direction (NeurIPS 2024)",
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"Gabliteration: SVD-based multi-direction extraction (arXiv:2512.18901)",
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"Norm-Preserving Biprojected Abliteration (grimjim, 2025)",
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"Young, Comparative Analysis of LLM Abliteration Methods (arXiv:2512.13655)",
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"Joad et al., More to Refusal than a Single Direction (2026)",
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"Heretic (p-e-w, 2025): Bayesian optimization, LoRA-mediated ablation, winsorization",
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"OBLITERATUS: Whitened SVD, EGA, CoT-aware, KL co-optimization, float interpolation (novel)"
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],
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"strong_layers": [
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],
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"n_harmful_prompts": 512,
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"n_harmless_prompts": 512,
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"quality_metrics": {
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"perplexity": 4.410901442250826,
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"coherence": 1.0,
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"refusal_rate": 0.0,
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"kl_divergence": 0.18998807668685913,
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"spectral_certification": "RED"
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},
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"kl_contributions": {},
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"cot_preserved_layers": [],
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"float_layer_weights": {},
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"lora_adapters_saved": false
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}
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{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='') %}{%- for message in messages %}{%- if message['role'] == 'system' %}{% set ns.system_prompt = message['content'] %}{%- endif %}{%- endfor %}{{bos_token}}{{ns.system_prompt}}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{{'<|User|>' + message['content']}}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is none %}{%- set ns.is_tool = false -%}{%- for tool in message['tool_calls']%}{%- if not ns.is_first %}{{'<|Assistant|><|tool▁calls▁begin|><|tool▁call▁begin|>' + tool['type'] + '<|tool▁sep|>' + tool['function']['name'] + '\n' + '```json' + '\n' + tool['function']['arguments'] + '\n' + '```' + '<|tool▁call▁end|>'}}{%- set ns.is_first = true -%}{%- else %}{{'\n' + '<|tool▁call▁begin|>' + tool['type'] + '<|tool▁sep|>' + tool['function']['name'] + '\n' + '```json' + '\n' + tool['function']['arguments'] + '\n' + '```' + '<|tool▁call▁end|>'}}{{'<|tool▁calls▁end|><|end▁of▁sentence|>'}}{%- endif %}{%- endfor %}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is not none %}{%- if ns.is_tool %}{{'<|tool▁outputs▁end|>' + message['content'] + '<|end▁of▁sentence|>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{% if '</think>' in content %}{% set content = content.split('</think>')[-1] %}{% endif %}{{'<|Assistant|>' + content + '<|end▁of▁sentence|>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<|tool▁outputs▁begin|><|tool▁output▁begin|>' + message['content'] + '<|tool▁output▁end|>'}}{%- set ns.is_output_first = false %}{%- else %}{{'\n<|tool▁output▁begin|>' + message['content'] + '<|tool▁output▁end|>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<|tool▁outputs▁end|>'}}{% endif %}{% if add_generation_prompt and not ns.is_tool %}{{'<|Assistant|><think>\n'}}{% endif %}
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{
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"architectures": [
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"Qwen2ForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 151643,
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"dtype": "float16",
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"eos_token_id": 151643,
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"hidden_act": "silu",
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"hidden_size": 5120,
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"initializer_range": 0.02,
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"intermediate_size": 27648,
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"layer_types": [
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"full_attention",
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"full_attention",
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"full_attention",
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],
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"max_position_embeddings": 131072,
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"max_window_layers": 64,
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"model_type": "qwen2",
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"num_attention_heads": 40,
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"num_hidden_layers": 64,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 1000000.0,
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"sliding_window": null,
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"tie_word_embeddings": false,
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"transformers_version": "4.57.6",
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"use_cache": true,
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"use_sliding_window": false,
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"vocab_size": 152064
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}
|
||||||
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Normal file
9
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Normal file
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|
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|
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"model.layers.8.self_attn.k_proj.weight": "model-00005-of-00034.safetensors",
|
||||||
|
"model.layers.8.self_attn.o_proj.weight": "model-00005-of-00034.safetensors",
|
||||||
|
"model.layers.8.self_attn.q_proj.bias": "model-00005-of-00034.safetensors",
|
||||||
|
"model.layers.8.self_attn.q_proj.weight": "model-00005-of-00034.safetensors",
|
||||||
|
"model.layers.8.self_attn.v_proj.bias": "model-00005-of-00034.safetensors",
|
||||||
|
"model.layers.8.self_attn.v_proj.weight": "model-00005-of-00034.safetensors",
|
||||||
|
"model.layers.9.input_layernorm.weight": "model-00006-of-00034.safetensors",
|
||||||
|
"model.layers.9.mlp.down_proj.weight": "model-00006-of-00034.safetensors",
|
||||||
|
"model.layers.9.mlp.gate_proj.weight": "model-00006-of-00034.safetensors",
|
||||||
|
"model.layers.9.mlp.up_proj.weight": "model-00006-of-00034.safetensors",
|
||||||
|
"model.layers.9.post_attention_layernorm.weight": "model-00006-of-00034.safetensors",
|
||||||
|
"model.layers.9.self_attn.k_proj.bias": "model-00006-of-00034.safetensors",
|
||||||
|
"model.layers.9.self_attn.k_proj.weight": "model-00006-of-00034.safetensors",
|
||||||
|
"model.layers.9.self_attn.o_proj.weight": "model-00006-of-00034.safetensors",
|
||||||
|
"model.layers.9.self_attn.q_proj.bias": "model-00006-of-00034.safetensors",
|
||||||
|
"model.layers.9.self_attn.q_proj.weight": "model-00006-of-00034.safetensors",
|
||||||
|
"model.layers.9.self_attn.v_proj.bias": "model-00006-of-00034.safetensors",
|
||||||
|
"model.layers.9.self_attn.v_proj.weight": "model-00006-of-00034.safetensors",
|
||||||
|
"model.norm.weight": "model-00033-of-00034.safetensors"
|
||||||
|
}
|
||||||
|
}
|
||||||
9
obliteratus_session.json
Normal file
9
obliteratus_session.json
Normal file
@@ -0,0 +1,9 @@
|
|||||||
|
{
|
||||||
|
"label": "advanced on DeepSeek-R1-Distill-Qwen-32B (16:35)",
|
||||||
|
"model_id": "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
|
||||||
|
"model_choice": "DeepSeek / DeepSeek-R1 Distill Qwen 32B",
|
||||||
|
"method": "advanced",
|
||||||
|
"dataset_key": "builtin",
|
||||||
|
"prompt_volume": -1,
|
||||||
|
"source": "obliterate"
|
||||||
|
}
|
||||||
23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
|||||||
|
{
|
||||||
|
"bos_token": {
|
||||||
|
"content": "<|begin▁of▁sentence|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false
|
||||||
|
},
|
||||||
|
"eos_token": {
|
||||||
|
"content": "<|end▁of▁sentence|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false
|
||||||
|
},
|
||||||
|
"pad_token": {
|
||||||
|
"content": "<|end▁of▁sentence|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false
|
||||||
|
}
|
||||||
|
}
|
||||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:e064ab12a3e3159997af01d74c52db62b097c176f14f24665d816d200bcb78e5
|
||||||
|
size 11423057
|
||||||
194
tokenizer_config.json
Normal file
194
tokenizer_config.json
Normal file
@@ -0,0 +1,194 @@
|
|||||||
|
{
|
||||||
|
"add_bos_token": true,
|
||||||
|
"add_eos_token": false,
|
||||||
|
"add_prefix_space": null,
|
||||||
|
"added_tokens_decoder": {
|
||||||
|
"151643": {
|
||||||
|
"content": "<|end▁of▁sentence|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151644": {
|
||||||
|
"content": "<|User|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151645": {
|
||||||
|
"content": "<|Assistant|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151646": {
|
||||||
|
"content": "<|begin▁of▁sentence|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151647": {
|
||||||
|
"content": "<|EOT|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151648": {
|
||||||
|
"content": "<think>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151649": {
|
||||||
|
"content": "</think>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151650": {
|
||||||
|
"content": "<|quad_start|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151651": {
|
||||||
|
"content": "<|quad_end|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151652": {
|
||||||
|
"content": "<|vision_start|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151653": {
|
||||||
|
"content": "<|vision_end|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151654": {
|
||||||
|
"content": "<|vision_pad|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151655": {
|
||||||
|
"content": "<|image_pad|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151656": {
|
||||||
|
"content": "<|video_pad|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151657": {
|
||||||
|
"content": "<tool_call>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151658": {
|
||||||
|
"content": "</tool_call>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151659": {
|
||||||
|
"content": "<|fim_prefix|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151660": {
|
||||||
|
"content": "<|fim_middle|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151661": {
|
||||||
|
"content": "<|fim_suffix|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151662": {
|
||||||
|
"content": "<|fim_pad|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151663": {
|
||||||
|
"content": "<|repo_name|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151664": {
|
||||||
|
"content": "<|file_sep|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"bos_token": "<|begin▁of▁sentence|>",
|
||||||
|
"clean_up_tokenization_spaces": false,
|
||||||
|
"eos_token": "<|end▁of▁sentence|>",
|
||||||
|
"extra_special_tokens": {},
|
||||||
|
"legacy": true,
|
||||||
|
"model_max_length": 16384,
|
||||||
|
"pad_token": "<|end▁of▁sentence|>",
|
||||||
|
"sp_model_kwargs": {},
|
||||||
|
"tokenizer_class": "LlamaTokenizerFast",
|
||||||
|
"unk_token": null,
|
||||||
|
"use_default_system_prompt": false
|
||||||
|
}
|
||||||
Reference in New Issue
Block a user