From c45de4d49b09f7ef6befe48df4068c77e222a77f Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Tue, 21 Jul 2026 22:43:43 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: absltnull/predBor-v1 Source: Original Platform --- .gitattributes | 35 + README.md | 74 + config.json | 32 + english_llm_eval_comparison.png | Bin 0 -> 89048 bytes generation_config.json | 10 + model.safetensors | 3 + optimizer.pt | 3 + predbor-logo.png | Bin 0 -> 20120 bytes rng_state.pth | 3 + scheduler.pt | 3 + serbian_llm_eval_comparison.png | Bin 0 -> 91786 bytes tokenizer.json | 260116 ++++++++++++++++++++++++++++ tokenizer_config.json | 26 + trainer_state.json | 263045 +++++++++++++++++++++++++++++ training_args.bin | 3 + 15 files changed, 523353 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 config.json create mode 100644 english_llm_eval_comparison.png create mode 100644 generation_config.json create mode 100644 model.safetensors create mode 100644 optimizer.pt create mode 100644 predbor-logo.png create mode 100644 rng_state.pth create mode 100644 scheduler.pt create mode 100644 serbian_llm_eval_comparison.png create mode 100644 tokenizer.json create mode 100644 tokenizer_config.json create mode 100644 trainer_state.json create mode 100644 training_args.bin diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..a6344aa --- /dev/null +++ b/.gitattributes @@ -0,0 +1,35 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..b698cb7 --- /dev/null +++ b/README.md @@ -0,0 +1,74 @@ +--- +license: mit +language: +- bs +- hr +- sr +- en +base_model: +- absltnull/predBor-v0.5 +pipeline_tag: text-generation +--- + +## predBor-v1 bs/sr/cr Small Language Model + +![predBor logo](./predbor-logo.png) + +*The new and shiny version, with better coherence and more brain power, in the same size as the preview.* + +### Overview +If you've seen the [preview](https://huggingface.co/absltnull/predBor-v0.5), you'll know exactly what this is. If not... + +predBor is the **first of its kind:** a small HBS language model **built from the ground up** to natively understand Bosnian, Croatian and Serbian, with English support. Unlike competitors such as `jerteh/gpt2-orao` or `gordicaleksa/YugoGPT`, **predBor is not based on any existing language model** like Mistral or GPT-2; it is its own original base model. + +### Model Details +- **Architecture:** LLaMA, +- **Context Length:** 4096, +- **Hidden Size:** 1536, +- **Num. Hidden Layers:** 24, +- **Num. Attention Heads:** 16, +- **Intermediate Size:** 4096, +- **Training Optimizer:** Lion, +- **Vocabulary Size:** 65k + +### Training Data +predBor was trained on approximately **22 billion tokens of diverse, fully uncensored, cleaned, processed and deduplicated HBS and English data**, making `Bor-CORPUS-22B` one of the largest collections of HBS data as of writing this. + +The dataset spans multiple sources and fields, such as songs, news articles, Wikipedia articles, entire books, *manually* scraped blogs, forums, erotica, conversations from multiple social media platforms (DMs, group chats, comment sections, forum discussions, etc.), cleaned CommonCrawl crawl and FineWeb text, and so on. + +Here are some sources from the dataset, as seen in the logs of my "cleaner and packer" script: +| Category | Total Count | Files | +|:---|---:|:---| +| **Web/Crawl** | 28,290,391 | cc-bosnian-huge.txt, dataset_done.txt, CC_2026.txt, fineweb-small.txt | +| **General/Language** | 14,817,407 | english.txt | +| **Data Split** | 3,997,195 | split.txt | +| **News/Blogs** | 1,089,621 | news_done.txt, oldnewspaper.txt, blogger_done.txt, news_out.txt, titlovi_blogs_output.txt | +| **Reference** | 257,932 | wikipedia_done.txt, wikiahh.txt, islamska_pitanja.txt, books_done.txt | +| **Social** | 92,396 | klixforums.txt, reddit.txt, insta.txt, discord.txt, viber.txt | +| **Other** | 32,375 | lrsum.txt, num_output.txt, sex_done.txt, mobi_output.txt, epub_output.txt | +| **Multimedia** | 14,677 | all_subtitles_combined.txt, lyrics.txt | + +### Model Evaluation +I've tested both versions of predBor against GPT-2 Orao, and the results were rather satisfying in some benchmarks. Take a look for yourself: + +#### Serbian-LLM-Eval by Gordić Aleksa +![Serbian LLM Eval Chart](./serbian_llm_eval_comparison.png) + +Out of the 9 Serbian-translated benchmarks, predBor has crushed GPT-2 Orao on 7 of them. + +#### English Eval (Same Benchmarks) +![English Benchmarks Chart](./english_llm_eval_comparison.png) + +As you can see, since GPT-2 Orao is based on GPT-2 (who would have guessed), it scores slightly higher than predBor in BoolQ, PiQA and WinoGrande, but gets absolutely demolished in ARC Easy, OpenBookQA, NQ Open and TriviaQA. + +### What's next? +**More data pretraining + instruct tuning.** + +**predBor-v2 will be a continued pretrain of this checkpoint**, trained on a massive uncensored, cleaned and language-labeled dataset of HBS and English data. + +Then, we get to instruct tuning. That's how we get the final version: **Bor**. + +**Pretraining Dataset Focus:** Human-written, clean, broad, uncensored text data. +**Instruct Dataset Focus:** Synthetic instruct-following data, trained only on one persona, no refusals baked in. + +Stay tuned. absltnull out. \ No newline at end of file diff --git a/config.json b/config.json new file mode 100644 index 0000000..3791c28 --- /dev/null +++ b/config.json @@ -0,0 +1,32 @@ +{ + "architectures": [ + "LlamaForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": 1, + "dtype": "float32", + "eos_token_id": 3, + "head_dim": 96, + "hidden_act": "silu", + "hidden_size": 1536, + "initializer_range": 0.02, + "intermediate_size": 4096, + "max_position_embeddings": 4096, + "mlp_bias": false, + "model_type": "llama", + "num_attention_heads": 16, + "num_hidden_layers": 24, + "num_key_value_heads": 16, + "pad_token_id": 3, + "pretraining_tp": 1, + "rms_norm_eps": 1e-05, + "rope_parameters": { + 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