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Model: sabari2005/cyberslm-33m-instruct
Source: Original Platform

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README.md

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+---
+license: apache-2.0
+language:
+- en
+pipeline_tag: text-generation
+library_name: transformers
+base_model: sabari2005/cyberslm-33m-base
+tags:
+- cybersecurity
+- small-language-model
+- instruct
+- sft
+- llama
+---
+
+# CyberSLM-33M-Instruct
+
+Instruction-tuned version of
+[`cyberslm-33m-base`](https://huggingface.co/sabari2005/cyberslm-33m-base) —
+a **33.5M-parameter cybersecurity-focused small language model** trained from
+scratch, then supervised-finetuned on **24,980 cybersecurity Q&A
+conversations** with loss masking on assistant tokens only.
+
+## Architecture
+
+Decoder-only transformer (Llama-style, loadable with `LlamaForCausalLM`):
+384 hidden / 12 layers / 6 heads / SwiGLU 1024 / RMSNorm / RoPE θ=10,000 /
+4096 context / 32k SentencePiece vocab / tied embeddings.
+Total: 33,531,264 parameters.
+
+## Chat format
+
+The model was finetuned with this template (built into `tokenizer.chat_template`):
+
+```
+<s>### User:
+{question}
+
+### Assistant:
+{answer}</s>
+```
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+tok = AutoTokenizer.from_pretrained("sabari2005/cyberslm-33m-instruct")
+model = AutoModelForCausalLM.from_pretrained("sabari2005/cyberslm-33m-instruct")
+
+messages = [{"role": "user", "content": "Explain what a SQL injection attack is and how to prevent it."}]
+ids = tok.apply_chat_template(messages, add_generation_prompt=True,
+                              return_tensors="pt", add_special_tokens=False)
+out = model.generate(ids, max_new_tokens=256, do_sample=True,
+                     temperature=0.7, top_p=0.9, eos_token_id=3, pad_token_id=0)
+print(tok.decode(out[0][ids.shape[1]:], skip_special_tokens=True))
+```
+
+> Note: the `<s>`/`</s>` markers in the template are literal text (the
+> SentencePiece vocab uses `<bos>`/`<eos>` pieces), matching exactly how the
+> model was trained. Use `apply_chat_template` and you don't need to think
+> about it.
+
+## Training
+
+- SFT on 24,980 cyber Q&A samples (multi-turn conversation format)
+- 3 epochs, LR 2e-5 cosine, AdamW β=(0.9, 0.95), wd 0.01, loss on assistant tokens only
+- Final val loss: **2.66**
+
+## Limitations
+
+33M parameters: strong at short cybersecurity explanations and Q&A; not
+suited for long-horizon reasoning, code generation, or general assistant
+duties. May hallucinate specifics (CVE numbers, tool flags) — verify facts.
+English only.

chat_template.jinja

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+{{ '<s>' }}{% if messages[0]['role'] == 'system' %}{{ 'System: ' + messages[0]['content'] | trim + '\n\n' }}{% set messages = messages[1:] %}{% endif %}{% for message in messages %}{% if message['role'] == 'user' %}{{ '### User:\n' + message['content'] | trim + '\n\n' }}{% elif message['role'] == 'assistant' %}{{ '### Assistant:\n' + message['content'] | trim + '</s>' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '### Assistant:\n' }}{% endif %}

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 2,
+  "dtype": "float32",
+  "eos_token_id": 3,
+  "head_dim": 64,
+  "hidden_act": "silu",
+  "hidden_size": 384,
+  "initializer_range": 0.02,
+  "intermediate_size": 1024,
+  "max_position_embeddings": 4096,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 6,
+  "num_hidden_layers": 12,
+  "num_key_value_heads": 6,
+  "pad_token_id": 0,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": true,
+  "transformers_version": "4.57.6",
+  "use_cache": true,
+  "vocab_size": 32000
+}

generation_config.json

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+{
+  "bos_token_id": 2,
+  "eos_token_id": 3,
+  "pad_token_id": 0,
+  "max_new_tokens": 256,
+  "do_sample": true,
+  "temperature": 0.7,
+  "top_p": 0.9
+}

model.safetensors

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+size 134137152

special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<bos>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<eos>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.model

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+size 735456

tokenizer_config.json

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+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "add_prefix_space": true,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<pad>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "<bos>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "3": {
+      "content": "<eos>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<bos>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<eos>",
+  "extra_special_tokens": {},
+  "legacy": false,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<pad>",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}