Text Classification
PEFT
Safetensors
English
Japanese
d1a
decision-model
calibration
lora
gemma4
typesafe
system-one
pull-requests
on-device
experimental
Instructions to use JohnP1/d1a-e2b-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use JohnP1/d1a-e2b-it with PEFT:
from peft import PeftModel from transformers import AutoModel base_model = AutoModel.from_pretrained("google/gemma-4-E2B-it") model = PeftModel.from_pretrained(base_model, "JohnP1/d1a-e2b-it") - Notebooks
- Google Colab
- Kaggle
File size: 3,729 Bytes
1d14f1a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 | {
"audio_token": "<|audio|>",
"backend": "tokenizers",
"boa_token": "<|audio>",
"boi_token": "<|image>",
"bos_token": "<bos>",
"eoa_token": "<audio|>",
"eoc_token": "<channel|>",
"eoi_token": "<image|>",
"eos_token": "<eos>",
"eot_token": "<turn|>",
"escape_token": "<|\"|>",
"etc_token": "<tool_call|>",
"etd_token": "<tool|>",
"etr_token": "<tool_response|>",
"extra_special_tokens": [
"<|video|>"
],
"image_token": "<|image|>",
"is_local": false,
"local_files_only": false,
"mask_token": "<mask>",
"model_max_length": 1000000000000000019884624838656,
"model_specific_special_tokens": {
"audio_token": "<|audio|>",
"boa_token": "<|audio>",
"boi_token": "<|image>",
"eoa_token": "<audio|>",
"eoc_token": "<channel|>",
"eoi_token": "<image|>",
"eot_token": "<turn|>",
"escape_token": "<|\"|>",
"etc_token": "<tool_call|>",
"etd_token": "<tool|>",
"etr_token": "<tool_response|>",
"image_token": "<|image|>",
"soc_token": "<|channel>",
"sot_token": "<|turn>",
"stc_token": "<|tool_call>",
"std_token": "<|tool>",
"str_token": "<|tool_response>",
"think_token": "<|think|>"
},
"pad_token": "<pad>",
"padding_side": "left",
"processor_class": "Gemma4Processor",
"response_schema": {
"properties": {
"content": {
"type": "string"
},
"role": {
"const": "assistant"
},
"thinking": {
"type": "string"
},
"tool_calls": {
"items": {
"properties": {
"function": {
"properties": {
"arguments": {
"additionalProperties": {},
"type": "object",
"x-parser": "gemma4-tool-call"
},
"name": {
"type": "string"
}
},
"type": "object",
"x-regex": "call\\:(?P<name>\\w+)(?P<arguments>\\{.*\\})"
},
"type": {
"const": "function"
}
},
"type": "object"
},
"type": "array",
"x-regex-iterator": "<\\|tool_call>(.*?)<tool_call\\|>"
}
},
"type": "object",
"x-regex": "(\\<\\|channel\\>thought\\n(?P<thinking>.*?)\\<channel\\|\\>)?(?P<tool_calls>\\<\\|tool_call\\>.*\\<tool_call\\|\\>)?(?P<content>(?:(?!\\<turn\\|\\>)(?!\\<\\|tool_response\\>).)+)?(?:\\<turn\\|\\>|\\<\\|tool_response\\>)?"
},
"response_template": {
"defaults": {
"role": "assistant"
},
"fields": {
"content": {
"close": [
"<turn|>",
"<|tool_response>",
"<eos>"
],
"content": "text"
},
"thinking": {
"close": "<channel|>",
"content": "text",
"open": "<|channel>thought\n"
},
"tool_calls": {
"close": "<tool_call|>",
"content": "json",
"content_args": {
"string_delims": [
[
"<|\"|>",
"<|\"|>"
]
],
"unquoted_keys": true
},
"open_pattern": "<\\|tool_call>call:(?P<name>\\w+)",
"repeats": true,
"transform": {
"function": {
"arguments": "{content}",
"name": "{name}"
},
"type": "function"
}
}
},
"start_anchor": [
"<|turn>model\n",
"<tool_response|>"
]
},
"soc_token": "<|channel>",
"sot_token": "<|turn>",
"stc_token": "<|tool_call>",
"std_token": "<|tool>",
"str_token": "<|tool_response>",
"think_token": "<|think|>",
"tokenizer_class": "GemmaTokenizer",
"unk_token": "<unk>"
}
|