Instructions to use Subject-Emu-5259/NeuralAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Subject-Emu-5259/NeuralAI with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
NeuralAI v2 merged: SmolLM2-360M + SFT v16/DPO v16 LoRA
Browse files- .gitattributes +0 -40
- README.md +38 -76
- chat_template.jinja +1 -6
- config.json +40 -0
- generation_config.json +7 -0
- model-00001-of-00003.safetensors +3 -0
- model-00002-of-00003.safetensors +3 -0
- model-00003-of-00003.safetensors +3 -0
- model.safetensors.index.json +298 -0
- tokenizer.json +28 -12
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README.md
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---
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library_name: peft
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model_name: NeuralAI
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model_type: adapter
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license: apache-2.0
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language:
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tags:
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- lora
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- peft
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- reasoning
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- debugging
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- edge-ai
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pipeline_tag: text-generation
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---
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# NeuralAI
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##
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##
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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from peft import PeftModel
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model =
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inputs =
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print(
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```
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## Training
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|---|---|
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| Method | DPO (Direct Preference Optimization) |
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| Dataset | 597 preference pairs (v15 expanded) |
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| Epochs | 3 |
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| Duration | ~12 minutes |
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| Completed | 2026-07-11 |
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## Framework versions
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- TRL: 0.24.0
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- Transformers: 4.57.6
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- PyTorch: 2.8.0
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## Use cases
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- **Code generation and debugging**: Multi-step reasoning for code correctness
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- **Logic and math**: Complex problem decomposition
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- **Edge deployment**: CPU-optimized for local/private AI
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- **Agentic workflows**: Tool-use and multi-step task execution
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## Citation
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```bibtex
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@inproceedings{rafailov2023direct,
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title = {{Direct Preference Optimization: Your Language Model is Secretly a Reward Model}},
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author = {Rafael Rafailov and Archit Sharma and Eric Mitchell and Christopher D. Manning and Stefano Ermon and Chelsea Finn},
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year = 2023,
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booktitle = {NeurIPS 2023},
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}
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```
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---
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library_name: transformers
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license: apache-2.0
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pipeline_tag: text-generation
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tags:
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- smollm2
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- lora
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- dpo
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- peft
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- neuralai
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base_model: HuggingFaceTB/SmolLM2-360M-Instruct
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model_name: NeuralAI v2
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---
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# NeuralAI v2 (merged)
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This repository hosts the **merged** weights of the [NeuralAI v2 LoRA + DPO adapter](https://huggingface.co/Subject-Emu-5259/NeuralAI/tree/main).
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It is the same model and tokenizer as the LoRA-only repo, but with the adapter weights fused into the base — load it directly without `peft.PeftModel.from_pretrained()`.
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## Model
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- **Base:** `HuggingFaceTB/SmolLM2-360M-Instruct`
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- **Adapter:** LoRA rank 16, alpha 32, dropout 0.05
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- **Method:** DPO preference alignment on top of SFT
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- **Params:** 361.8M
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- **License:** Apache-2.0
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- **Framework:** PyTorch + Transformers 5.5.4 + PEFT 0.19.0
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## How to load
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```python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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repo = "Subject-Emu-5259/NeuralAI" # this repo
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tok = AutoTokenizer.from_pretrained(repo)
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model = AutoModelForCausalLM.from_pretrained(repo, dtype=torch.bfloat16, device_map="auto")
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prompt = "NeuralAI is"
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inputs = tok(prompt, return_tensors="pt").to(model.device)
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out = model.generate(**inputs, max_new_tokens=80, do_sample=True, top_p=0.9, temperature=0.7)
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print(tok.decode(out[0], skip_special_tokens=True))
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```
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## Training
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| Field | Value |
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|---|---|
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| Method | LoRA + DPO preference alignment |
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| Epochs | 3 |
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| Learning rate | 2e-4 |
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| Train / val | 363 / 41 |
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| Duration | ~26 min |
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| Completed | 2026-05-17 |
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| Framework | PyTorch + Transformers + PEFT 0.19.0 |
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By De'Andrew P. Harris. NeuralAI is part of the NeuralAI / NeuralLabs product stack.
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chat_template.jinja
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{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system
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You are a helpful AI assistant named SmolLM, trained by Hugging Face<|im_end|>
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' }}{% endif %}{{'<|im_start|>' + message['role'] + '
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' + message['content'] + '<|im_end|>' + '
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'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
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' }}{% endif %}
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{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are NeuralAI, a production-grade artificial intelligence system developed by De’Andrew Preston Harris. You are brilliant, professional, and collaborative.<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}
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config.json
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{
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"dtype": "float32",
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"eos_token_id": 2,
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"head_dim": 64,
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"hidden_act": "silu",
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"hidden_size": 960,
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"initializer_range": 0.02,
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"intermediate_size": 2560,
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"is_llama_config": true,
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"max_position_embeddings": 8192,
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"mlp_bias": false,
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"model_type": "llama",
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| 19 |
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"num_attention_heads": 15,
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| 20 |
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"num_hidden_layers": 32,
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"num_key_value_heads": 5,
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| 22 |
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"pad_token_id": 2,
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| 23 |
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_interleaved": false,
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"rope_parameters": {
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"rope_theta": 100000,
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"rope_type": "default"
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},
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"tie_word_embeddings": true,
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"transformers.js_config": {
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"kv_cache_dtype": {
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"fp16": "float16",
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"q4f16": "float16"
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}
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},
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"transformers_version": "5.5.4",
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"use_cache": true,
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"vocab_size": 49152
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"pad_token_id": 2,
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"transformers_version": "5.5.4"
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}
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model-00001-of-00003.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:401ccff316fc2c4b2556b5f91443038f433b87b193afb7e6212617c38860e9f8
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size 498470624
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model-00002-of-00003.safetensors
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version https://git-lfs.github.com/spec/v1
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size 496543816
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model-00003-of-00003.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:d7652a4066e250de092a8641bad89be1de396a65ade684924d9565896208246d
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size 452302392
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model.safetensors.index.json
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tokenizer.json
CHANGED
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@@ -159,21 +159,37 @@
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|
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|
@@ -184,8 +200,8 @@
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"type": "TemplateProcessing",
|
| 169 |
+
"single": [
|
| 170 |
{
|
| 171 |
+
"Sequence": {
|
| 172 |
+
"id": "A",
|
| 173 |
+
"type_id": 0
|
| 174 |
+
}
|
| 175 |
+
}
|
| 176 |
+
],
|
| 177 |
+
"pair": [
|
| 178 |
+
{
|
| 179 |
+
"Sequence": {
|
| 180 |
+
"id": "A",
|
| 181 |
+
"type_id": 0
|
| 182 |
+
}
|
| 183 |
},
|
| 184 |
{
|
| 185 |
+
"Sequence": {
|
| 186 |
+
"id": "B",
|
| 187 |
+
"type_id": 1
|
| 188 |
+
}
|
| 189 |
}
|
| 190 |
+
],
|
| 191 |
+
"special_tokens": {}
|
| 192 |
},
|
|
|
|
| 193 |
"decoder": {
|
| 194 |
"type": "ByteLevel",
|
| 195 |
"add_prefix_space": true,
|
|
|
|
| 200 |
"type": "BPE",
|
| 201 |
"dropout": null,
|
| 202 |
"unk_token": null,
|
| 203 |
+
"continuing_subword_prefix": "",
|
| 204 |
+
"end_of_word_suffix": "",
|
| 205 |
"fuse_unk": false,
|
| 206 |
"byte_fallback": false,
|
| 207 |
"ignore_merges": false,
|