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- LICENSE +121 -0
- NOTICE +1 -0
- README.md +142 -0
- config.json +32 -0
- generation_config.json +10 -0
- model.safetensors +3 -0
- special_tokens_map.json +24 -0
- tokenizer.json +0 -0
- tokenizer_config.json +215 -0
- violet.png +3 -0
.gitattributes
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LICENSE
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violet.png is © @rose.grtqndl (Instagram). Used and redistributed with permission. Copyright remains with the artist.
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README.md
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---
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license: cc0-1.0
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---
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| 1 |
---
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| 2 |
+
language:
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- en
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+
library_name: transformers
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| 5 |
+
tags:
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| 6 |
+
- text-generation
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| 7 |
+
- gpt_neox
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- roleplay
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| 9 |
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- victorian
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license: cc0-1.0
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---
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+
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+
# Violet 160M — Victorian-era Text Completions
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| 14 |
+
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| 15 |
+

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+
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+
## Model Summary
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| 18 |
+
**Violet** 160M is a GPT-NeoX base model built to provide text completions for Victorian era text. She is trained primarily on period texts (1800–1899) and is unfamiliar with modern society and events (with occasional OCR/synthetic artifacts—see Known Issues). Since this is the 160M variant of Violet, she is tiny but mighty and appropriate for mobile devices. For completions, Violet 160M is almost as good as Violet 1b4. Violet 160M consistently punches above her paygrade in terms of output providing rich depth of narrative prose, with albeit somewhat simplistic reasoning. If you're looking for the most powerful Violet, have a visit to [Violet 1b4 Chat](zakarth/violet-1b4-chat). Violet 160M provided some a portion of the synthetic data corpus for Violet 1B4 training.
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+
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+
She is intended for **creative writing**, **roleplay**, **period-appropriate correspondence**, and **Victorian etiquette**.
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| 21 |
+
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+
- Architecture: `GPTNeoXForCausalLM`
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| 23 |
+
- Parameters: ~152M
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| 24 |
+
- Context length: 4096
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| 25 |
+
- Vocab size: 50281
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| 26 |
+
- Tokenizer: `GPTNeoXTokenizer`
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| 27 |
+
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| 28 |
+
## Intended Use
|
| 29 |
+
**Good for**
|
| 30 |
+
- Victorian-flavored conversation and letters
|
| 31 |
+
- Descriptive prose, scene writing, etiquette Q&A
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| 32 |
+
|
| 33 |
+
**Not good for**
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| 34 |
+
- Contemporary factual Q&A
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| 35 |
+
- Medical/legal/financial advice
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| 36 |
+
|
| 37 |
+
## Known Issues / Limitations
|
| 38 |
+
- The 160M model series are very brittle in chat, but are very good at text completion in general.
|
| 39 |
+
- Ages and dates are unreliable (even within 1800–1899).
|
| 40 |
+
- Because parts of the corpus were derived from OCR, occasional stray modern tokens may appear (e.g., “http”, “Google”, “Internet Archive”).
|
| 41 |
+
- Training data includes UK and US English from the era.
|
| 42 |
+
- The 160M model series did not pre-filter only English in the corpus, meaning other languages were added as part of its pretraining. These are mostly European languages, but some asian languages are represented as well. In practice this is mostly a curiosity as Violet 160M can perform some basic text completions in French.
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| 43 |
+
- Outputs may reflect historical biases typical of the Victorian era. Use discretion.
|
| 44 |
+
|
| 45 |
+
## Notes
|
| 46 |
+
Violet is not the first LLM trained on a historical-only pretraining corpus; to the author’s knowledge that distinction belongs to **TimeCapsuleLLM**. Violet was developed independently, and differs in:
|
| 47 |
+
- The sizes of the models
|
| 48 |
+
- The range of dates used in pretraining
|
| 49 |
+
- Different (albeit in some cases certainly overlapping) pretraining data
|
| 50 |
+
|
| 51 |
+
Violet 160M was built on a corpus spanning 1800–1899 mostly sourced from Project Gutenberg. Consequently she has a very strong narrative presence and punches above her model size in terms of quality of text.
|
| 52 |
+
|
| 53 |
+
This project began as an attempt to build a local LLM without relying on copyrighted training sources. The author also values local models that can run on a user’s machine without sending data to the cloud.
|
| 54 |
+
|
| 55 |
+
## Demo Resources
|
| 56 |
+
- HF Space: [Transformers.js Demo](Zakarth/violetdemo)
|
| 57 |
+
- CloudFlare Mirror: [Transformers.js Demo](https://pub-353f427e6227415cb077f3645638c125.r2.dev/index.html)
|
| 58 |
+
- Both of these are intended to use WebGPU and run local on your system -- No data is sent to the cloud.
|
| 59 |
+
|
| 60 |
+
## Related repos
|
| 61 |
+
- `Zakarth/violet-160m-chat` (base/completion for 160M series)
|
| 62 |
+
- `Zakarth/violet-1b4` (base/completion)
|
| 63 |
+
- `Zakarth/violet-1b4-chat-onnx` (WebGPU INT8)
|
| 64 |
+
|
| 65 |
+
## Prompt Format
|
| 66 |
+
Use this structure:
|
| 67 |
+
|
| 68 |
+
```text
|
| 69 |
+
{input...}
|
| 70 |
+
```
|
| 71 |
+
|
| 72 |
+
The model will then generate:
|
| 73 |
+
|
| 74 |
+
```text
|
| 75 |
+
{completion...}
|
| 76 |
+
```
|
| 77 |
+
|
| 78 |
+
## Tokenization and Special Tokens
|
| 79 |
+
Violet 160M uses a GPT-NeoX / Pythia-style tokenizer.
|
| 80 |
+
|
| 81 |
+
Recommended IDs for generation:
|
| 82 |
+
* eos_token_id: 0
|
| 83 |
+
|
| 84 |
+
!! Do not mix tokenizers from other Violet variants (e.g. 1.4B) with this model.
|
| 85 |
+
|
| 86 |
+
## How to use (Transformers)
|
| 87 |
+
```code
|
| 88 |
+
from transformers import AutoTokenizer, AutoModelForCausalLM
|
| 89 |
+
import torch
|
| 90 |
+
|
| 91 |
+
repo = "Zakarth/violet-160m"
|
| 92 |
+
tok = AutoTokenizer.from_pretrained(repo, use_fast=True)
|
| 93 |
+
model = AutoModelForCausalLM.from_pretrained(repo, device_map="auto")
|
| 94 |
+
|
| 95 |
+
prompt = "The fog slowly lifted"
|
| 96 |
+
|
| 97 |
+
inputs = tok(prompt, return_tensors="pt", add_special_tokens=False)
|
| 98 |
+
# Filter out token_type_ids if present
|
| 99 |
+
inputs = {k: v.to(model.device) for k, v in inputs.items() if k in ['input_ids', 'attention_mask']}
|
| 100 |
+
|
| 101 |
+
out = model.generate(
|
| 102 |
+
**inputs,
|
| 103 |
+
max_new_tokens=180,
|
| 104 |
+
do_sample=True,
|
| 105 |
+
temperature=0.8,
|
| 106 |
+
top_p=0.9,
|
| 107 |
+
top_k=40,
|
| 108 |
+
repetition_penalty=1.15,
|
| 109 |
+
eos_token_id=0,
|
| 110 |
+
pad_token_id=50277,
|
| 111 |
+
)
|
| 112 |
+
print(tok.decode(out[0][inputs["input_ids"].shape[1]:], skip_special_tokens=False))
|
| 113 |
+
```
|
| 114 |
+
|
| 115 |
+
## Sample Outputs
|
| 116 |
+
|
| 117 |
+
> The King spoke thusly
|
| 118 |
+
|
| 119 |
+
```text
|
| 120 |
+
"My gracious mistress, I will not be so ungracious to you as to have you with me. My presence is not needed by us; we are strangers in the land of my fathers." "I am not ungrateful, sir," replied she, "but I desire not the intrusion of strangers into my own domain.Nor do I think it strange that you should remain here so long and so pleasantly." "I am ready to become your friend, since I claim all this honour," said he, "and the absence of strangers here, has made me happy. Your absence is not without its compensations, for I have given my daughter into the hands of a father, who was no common man.He was a man of great wealth, and had always been friendly towards her. He was fond of her, and was kind to her, but there were many reasons why we should not part company in society, and he loved her. She was a stranger to him, and he knew her well.She would never have consented to his wedded life, and he was sure that she would never consent to this marriage, which would make the union between us a hard one. We have no right to associate with others, except on account of our parents' death, and therefore you must decide for yourself. When the day of separation comes, you must return to my house, and to be my guests until the nuptials are over.This is my first request
|
| 121 |
+
```
|
| 122 |
+
|
| 123 |
+
## License
|
| 124 |
+
|
| 125 |
+
Model weights and code in this repository are released under CC0 1.0 (public domain dedication).
|
| 126 |
+
|
| 127 |
+
## Artwork
|
| 128 |
+
|
| 129 |
+
violet.png is © @rose.grtqndl (Instagram). Used and redistributed with permission; copyright remains with the artist.
|
| 130 |
+
|
| 131 |
+
## Contact
|
| 132 |
+
|
| 133 |
+
You may contact me on X or anywhere else by searching for my handle
|
| 134 |
+
|
| 135 |
+
## Citation
|
| 136 |
+
|
| 137 |
+
```bibtex
|
| 138 |
+
@misc{violet2026,
|
| 139 |
+
author = Zakarth,
|
| 140 |
+
title = {Violet: Victorian Language Models},
|
| 141 |
+
year = {2026},
|
| 142 |
+
publisher = {HuggingFace},
|
| 143 |
+
url = {https://huggingface.co/Zakarth/violet-1b4-chat}
|
| 144 |
+
}
|
| 145 |
+
```
|
config.json
ADDED
|
@@ -0,0 +1,32 @@
|
|
|
|
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|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"GPTNeoXForCausalLM"
|
| 4 |
+
],
|
| 5 |
+
"attention_bias": true,
|
| 6 |
+
"attention_dropout": 0.0,
|
| 7 |
+
"bos_token_id": 0,
|
| 8 |
+
"classifier_dropout": 0.1,
|
| 9 |
+
"dtype": "bfloat16",
|
| 10 |
+
"eos_token_id": 0,
|
| 11 |
+
"hidden_act": "gelu",
|
| 12 |
+
"hidden_dropout": 0.0,
|
| 13 |
+
"hidden_size": 768,
|
| 14 |
+
"initializer_range": 0.02,
|
| 15 |
+
"intermediate_size": 3072,
|
| 16 |
+
"layer_norm_eps": 1e-05,
|
| 17 |
+
"max_position_embeddings": 4096,
|
| 18 |
+
"model_type": "gpt_neox",
|
| 19 |
+
"num_attention_heads": 12,
|
| 20 |
+
"num_hidden_layers": 16,
|
| 21 |
+
"pad_token_id": 0,
|
| 22 |
+
"partial_rotary_factor": 0.25,
|
| 23 |
+
"rope_scaling": null,
|
| 24 |
+
"rope_theta": 10000,
|
| 25 |
+
"rotary_emb_base": 10000,
|
| 26 |
+
"rotary_pct": 0.25,
|
| 27 |
+
"tie_word_embeddings": true,
|
| 28 |
+
"transformers_version": "4.57.1",
|
| 29 |
+
"use_cache": true,
|
| 30 |
+
"use_parallel_residual": true,
|
| 31 |
+
"vocab_size": 50277
|
| 32 |
+
}
|
generation_config.json
ADDED
|
@@ -0,0 +1,10 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_from_model_config": true,
|
| 3 |
+
"bos_token_id": 0,
|
| 4 |
+
"eos_token_id": [
|
| 5 |
+
0,
|
| 6 |
+
2
|
| 7 |
+
],
|
| 8 |
+
"pad_token_id": 0,
|
| 9 |
+
"transformers_version": "4.57.1"
|
| 10 |
+
}
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:724a0f96de50bca964c1469091e65d5050209588ec9013d3c5fe1cac861765f2
|
| 3 |
+
size 304063008
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1,24 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token": {
|
| 3 |
+
"content": "<|endoftext|>",
|
| 4 |
+
"lstrip": false,
|
| 5 |
+
"normalized": false,
|
| 6 |
+
"rstrip": false,
|
| 7 |
+
"single_word": false
|
| 8 |
+
},
|
| 9 |
+
"eos_token": {
|
| 10 |
+
"content": "<|endoftext|>",
|
| 11 |
+
"lstrip": false,
|
| 12 |
+
"normalized": false,
|
| 13 |
+
"rstrip": false,
|
| 14 |
+
"single_word": false
|
| 15 |
+
},
|
| 16 |
+
"pad_token": "<|endoftext|>",
|
| 17 |
+
"unk_token": {
|
| 18 |
+
"content": "<|endoftext|>",
|
| 19 |
+
"lstrip": false,
|
| 20 |
+
"normalized": false,
|
| 21 |
+
"rstrip": false,
|
| 22 |
+
"single_word": false
|
| 23 |
+
}
|
| 24 |
+
}
|
tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,215 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
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|
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|
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|
|
|
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|
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|
|
|
|
|
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|
|
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|
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|
|
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|
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|
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|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_bos_token": false,
|
| 3 |
+
"add_eos_token": false,
|
| 4 |
+
"add_prefix_space": false,
|
| 5 |
+
"added_tokens_decoder": {
|
| 6 |
+
"0": {
|
| 7 |
+
"content": "<|endoftext|>",
|
| 8 |
+
"lstrip": false,
|
| 9 |
+
"normalized": false,
|
| 10 |
+
"rstrip": false,
|
| 11 |
+
"single_word": false,
|
| 12 |
+
"special": true
|
| 13 |
+
},
|
| 14 |
+
"1": {
|
| 15 |
+
"content": "<|padding|>",
|
| 16 |
+
"lstrip": false,
|
| 17 |
+
"normalized": false,
|
| 18 |
+
"rstrip": false,
|
| 19 |
+
"single_word": false,
|
| 20 |
+
"special": true
|
| 21 |
+
},
|
| 22 |
+
"50254": {
|
| 23 |
+
"content": " ",
|
| 24 |
+
"lstrip": false,
|
| 25 |
+
"normalized": true,
|
| 26 |
+
"rstrip": false,
|
| 27 |
+
"single_word": false,
|
| 28 |
+
"special": false
|
| 29 |
+
},
|
| 30 |
+
"50255": {
|
| 31 |
+
"content": " ",
|
| 32 |
+
"lstrip": false,
|
| 33 |
+
"normalized": true,
|
| 34 |
+
"rstrip": false,
|
| 35 |
+
"single_word": false,
|
| 36 |
+
"special": false
|
| 37 |
+
},
|
| 38 |
+
"50256": {
|
| 39 |
+
"content": " ",
|
| 40 |
+
"lstrip": false,
|
| 41 |
+
"normalized": true,
|
| 42 |
+
"rstrip": false,
|
| 43 |
+
"single_word": false,
|
| 44 |
+
"special": false
|
| 45 |
+
},
|
| 46 |
+
"50257": {
|
| 47 |
+
"content": " ",
|
| 48 |
+
"lstrip": false,
|
| 49 |
+
"normalized": true,
|
| 50 |
+
"rstrip": false,
|
| 51 |
+
"single_word": false,
|
| 52 |
+
"special": false
|
| 53 |
+
},
|
| 54 |
+
"50258": {
|
| 55 |
+
"content": " ",
|
| 56 |
+
"lstrip": false,
|
| 57 |
+
"normalized": true,
|
| 58 |
+
"rstrip": false,
|
| 59 |
+
"single_word": false,
|
| 60 |
+
"special": false
|
| 61 |
+
},
|
| 62 |
+
"50259": {
|
| 63 |
+
"content": " ",
|
| 64 |
+
"lstrip": false,
|
| 65 |
+
"normalized": true,
|
| 66 |
+
"rstrip": false,
|
| 67 |
+
"single_word": false,
|
| 68 |
+
"special": false
|
| 69 |
+
},
|
| 70 |
+
"50260": {
|
| 71 |
+
"content": " ",
|
| 72 |
+
"lstrip": false,
|
| 73 |
+
"normalized": true,
|
| 74 |
+
"rstrip": false,
|
| 75 |
+
"single_word": false,
|
| 76 |
+
"special": false
|
| 77 |
+
},
|
| 78 |
+
"50261": {
|
| 79 |
+
"content": " ",
|
| 80 |
+
"lstrip": false,
|
| 81 |
+
"normalized": true,
|
| 82 |
+
"rstrip": false,
|
| 83 |
+
"single_word": false,
|
| 84 |
+
"special": false
|
| 85 |
+
},
|
| 86 |
+
"50262": {
|
| 87 |
+
"content": " ",
|
| 88 |
+
"lstrip": false,
|
| 89 |
+
"normalized": true,
|
| 90 |
+
"rstrip": false,
|
| 91 |
+
"single_word": false,
|
| 92 |
+
"special": false
|
| 93 |
+
},
|
| 94 |
+
"50263": {
|
| 95 |
+
"content": " ",
|
| 96 |
+
"lstrip": false,
|
| 97 |
+
"normalized": true,
|
| 98 |
+
"rstrip": false,
|
| 99 |
+
"single_word": false,
|
| 100 |
+
"special": false
|
| 101 |
+
},
|
| 102 |
+
"50264": {
|
| 103 |
+
"content": " ",
|
| 104 |
+
"lstrip": false,
|
| 105 |
+
"normalized": true,
|
| 106 |
+
"rstrip": false,
|
| 107 |
+
"single_word": false,
|
| 108 |
+
"special": false
|
| 109 |
+
},
|
| 110 |
+
"50265": {
|
| 111 |
+
"content": " ",
|
| 112 |
+
"lstrip": false,
|
| 113 |
+
"normalized": true,
|
| 114 |
+
"rstrip": false,
|
| 115 |
+
"single_word": false,
|
| 116 |
+
"special": false
|
| 117 |
+
},
|
| 118 |
+
"50266": {
|
| 119 |
+
"content": " ",
|
| 120 |
+
"lstrip": false,
|
| 121 |
+
"normalized": true,
|
| 122 |
+
"rstrip": false,
|
| 123 |
+
"single_word": false,
|
| 124 |
+
"special": false
|
| 125 |
+
},
|
| 126 |
+
"50267": {
|
| 127 |
+
"content": " ",
|
| 128 |
+
"lstrip": false,
|
| 129 |
+
"normalized": true,
|
| 130 |
+
"rstrip": false,
|
| 131 |
+
"single_word": false,
|
| 132 |
+
"special": false
|
| 133 |
+
},
|
| 134 |
+
"50268": {
|
| 135 |
+
"content": " ",
|
| 136 |
+
"lstrip": false,
|
| 137 |
+
"normalized": true,
|
| 138 |
+
"rstrip": false,
|
| 139 |
+
"single_word": false,
|
| 140 |
+
"special": false
|
| 141 |
+
},
|
| 142 |
+
"50269": {
|
| 143 |
+
"content": " ",
|
| 144 |
+
"lstrip": false,
|
| 145 |
+
"normalized": true,
|
| 146 |
+
"rstrip": false,
|
| 147 |
+
"single_word": false,
|
| 148 |
+
"special": false
|
| 149 |
+
},
|
| 150 |
+
"50270": {
|
| 151 |
+
"content": " ",
|
| 152 |
+
"lstrip": false,
|
| 153 |
+
"normalized": true,
|
| 154 |
+
"rstrip": false,
|
| 155 |
+
"single_word": false,
|
| 156 |
+
"special": false
|
| 157 |
+
},
|
| 158 |
+
"50271": {
|
| 159 |
+
"content": " ",
|
| 160 |
+
"lstrip": false,
|
| 161 |
+
"normalized": true,
|
| 162 |
+
"rstrip": false,
|
| 163 |
+
"single_word": false,
|
| 164 |
+
"special": false
|
| 165 |
+
},
|
| 166 |
+
"50272": {
|
| 167 |
+
"content": " ",
|
| 168 |
+
"lstrip": false,
|
| 169 |
+
"normalized": true,
|
| 170 |
+
"rstrip": false,
|
| 171 |
+
"single_word": false,
|
| 172 |
+
"special": false
|
| 173 |
+
},
|
| 174 |
+
"50273": {
|
| 175 |
+
"content": " ",
|
| 176 |
+
"lstrip": false,
|
| 177 |
+
"normalized": true,
|
| 178 |
+
"rstrip": false,
|
| 179 |
+
"single_word": false,
|
| 180 |
+
"special": false
|
| 181 |
+
},
|
| 182 |
+
"50274": {
|
| 183 |
+
"content": " ",
|
| 184 |
+
"lstrip": false,
|
| 185 |
+
"normalized": true,
|
| 186 |
+
"rstrip": false,
|
| 187 |
+
"single_word": false,
|
| 188 |
+
"special": false
|
| 189 |
+
},
|
| 190 |
+
"50275": {
|
| 191 |
+
"content": " ",
|
| 192 |
+
"lstrip": false,
|
| 193 |
+
"normalized": true,
|
| 194 |
+
"rstrip": false,
|
| 195 |
+
"single_word": false,
|
| 196 |
+
"special": false
|
| 197 |
+
},
|
| 198 |
+
"50276": {
|
| 199 |
+
"content": " ",
|
| 200 |
+
"lstrip": false,
|
| 201 |
+
"normalized": true,
|
| 202 |
+
"rstrip": false,
|
| 203 |
+
"single_word": false,
|
| 204 |
+
"special": false
|
| 205 |
+
}
|
| 206 |
+
},
|
| 207 |
+
"bos_token": "<|endoftext|>",
|
| 208 |
+
"clean_up_tokenization_spaces": false,
|
| 209 |
+
"eos_token": "<|endoftext|>",
|
| 210 |
+
"extra_special_tokens": {},
|
| 211 |
+
"model_max_length": 1000000000000000019884624838656,
|
| 212 |
+
"pad_token": "<|endoftext|>",
|
| 213 |
+
"tokenizer_class": "GPTNeoXTokenizer",
|
| 214 |
+
"unk_token": "<|endoftext|>"
|
| 215 |
+
}
|
violet.png
ADDED
|
Git LFS Details
|