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README.md

@@ -1,22 +1,228 @@
 ---
 license: apache-2.0
-base_model: allenai/Olmo-Hybrid-Instruct-SFT-7B
-base_model_relation: quantized
-quantized_by: turboderp
-tags:
-- exl3
+datasets:
+- allenai/Dolci-Instruct-SFT-Tool-Use-SA
+- allenai/Dolci-Instruct-SFT
+language:
+- en
+base_model:
+- allenai/Olmo-Hybrid-7B
+library_name: transformers
 ---
+## Model Details
 
-EXL3 quants of [Olmo-Hybrid-Instruct-SFT-7B](https://huggingface.co/allenai/Olmo-Hybrid-Instruct-SFT-7B)
 
-⚠️ Requires ExLlamaV3 v0.0.26 (or v0.0.25 `dev` branch)
+# Model Card for Olmo Hybrid Instruct SFT
 
-[2.00 bits per weight](https://huggingface.co/turboderp/Olmo-Hybrid-Instruct-SFT-7B-exl3/tree/2.00bpw)    
-[2.50 bits per weight](https://huggingface.co/turboderp/Olmo-Hybrid-Instruct-SFT-7B-exl3/tree/2.50bpw)    
-[3.00 bits per weight](https://huggingface.co/turboderp/Olmo-Hybrid-Instruct-SFT-7B-exl3/tree/3.00bpw)    
-[3.50 bits per weight](https://huggingface.co/turboderp/Olmo-Hybrid-Instruct-SFT-7B-exl3/tree/3.50bpw)    
-[4.00 bits per weight](https://huggingface.co/turboderp/Olmo-Hybrid-Instruct-SFT-7B-exl3/tree/4.00bpw)    
-[5.00 bits per weight](https://huggingface.co/turboderp/Olmo-Hybrid-Instruct-SFT-7B-exl3/tree/5.00bpw)    
-[6.00 bits per weight](https://huggingface.co/turboderp/Olmo-Hybrid-Instruct-SFT-7B-exl3/tree/6.00bpw)    
+We expand on our Olmo model series by introducing Olmo Hybrid, a new 7B hybrid RNN model in the Olmo family. Olmo Hybrid dramatically outperforms Olmo 3 in final performance, consistently showing roughly 2x data
+efficiency on core evals over the course of our pretraining run. We also show gains in performance on long-context benchmarks, as well as improved inference efficiency
+(throughput and memory) on long-context lengths by a factor of 75%.
 
-![kld](https://cdn-uploads.huggingface.co/production/uploads/6383dc174c48969dcf1b4fce/uaFw4Q9IGpy2Xm52o46wB.png)
+The core models released in this batch include the following:
+
+| **Stage**               | **Olmo 3 7B Think** | **Olmo 3 32B Think** | **Olmo 3 7B Instruct** | **Olmo Hybrid Think 7B** | **Olmo Hybrid Instruct 7B** |
+|--------------------------|-----------------------|------------------------|---------------------------|-------------------------------|----------------------------------|
+| **Base Model**           | [Olmo-3-7B](https://huggingface.co/allenai/Olmo-3-1025-7B) | [Olmo-3-32B](https://huggingface.co/allenai/Olmo-3-1125-32B) | [Olmo-3-7B](https://huggingface.co/allenai/Olmo-3-1025-7B) | [Olmo-Hybrid-7B](https://huggingface.co/allenai/Olmo-Hybrid-7B) | [Olmo-Hybrid-7B](https://huggingface.co/allenai/Olmo-Hybrid-7B) |
+| **SFT**                  | [Olmo-3-7B-Think-SFT](https://huggingface.co/allenai/Olmo-3-7B-Think-SFT) | [Olmo-3-32B-Think-SFT](https://huggingface.co/allenai/Olmo-3-32B-Think-SFT) | [Olmo-3-7B-Instruct-SFT](https://huggingface.co/allenai/Olmo-3-7B-Instruct-SFT) | [Olmo-Hybrid-Think-SFT-7B](https://huggingface.co/allenai/Olmo-Hybrid-Think-SFT-7B) | [Olmo-Hybrid-Instruct-SFT-7B](https://huggingface.co/allenai/Olmo-Hybrid-Instruct-SFT-7B) |
+| **DPO**                  | [Olmo-3-7B-Think-DPO](https://huggingface.co/allenai/Olmo-3-7B-Think-DPO) | [Olmo-3-32B-Think-DPO](https://huggingface.co/allenai/Olmo-3-32B-Think-DPO) | [Olmo-3-7B-Instruct-DPO](https://huggingface.co/allenai/Olmo-3-7B-Instruct-DPO) | -- | [Olmo-Hybrid-Instruct-DPO-7B](https://huggingface.co/allenai/Olmo-Hybrid-Instruct-DPO-7B) |
+| **Final Models (RLVR)**  | [Olmo-3-7B-Think](https://huggingface.co/allenai/Olmo-3-7B-Think) | [Olmo-3-32B-Think](https://huggingface.co/allenai/Olmo-3-32B-Think) | [Olmo-3-7B-Instruct](https://huggingface.co/allenai/Olmo-3-7B-Instruct) | -- | -- |
+
+
+Olmo is a series of **O**pen **l**anguage **mo**dels designed to enable the science of language models. 
+These models are pre-trained on the Dolma 3 dataset and post-trained on the Dolci datasets. We are releasing all code, checkpoints, logs (coming soon), and associated training details. 
+            
+
+## Installation
+
+Olmo Hybrid is supported in transformers 5.3.0 or higher:
+```bash
+pip install transformers>=5.3.0
+```
+
+## Inference
+
+You can use OLMo with the standard HuggingFace transformers library:
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+olmo = AutoModelForCausalLM.from_pretrained("allenai/Olmo-Hybrid-Instruct-SFT-7B")
+tokenizer = AutoTokenizer.from_pretrained("allenai/Olmo-Hybrid-Instruct-SFT-7B")
+message = ["Who would win in a fight - a dinosaur or a cow named Moo Moo?"]
+inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
+# optional verifying cuda
+# inputs = {k: v.to('cuda') for k,v in inputs.items()}
+# olmo = olmo.to('cuda')
+response = olmo.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
+print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
+>> '<think>Okay, so the question is who would win in a fight...'
+```
+
+For faster performance, you can quantize the model using the following method:
+```python
+AutoModelForCausalLM.from_pretrained("allenai/Olmo-Hybrid-Instruct-SFT-7B", 
+    torch_dtype=torch.float16, 
+    load_in_8bit=True)  # Requires bitsandbytes
+```
+The quantized model is more sensitive to data types and CUDA operations. To avoid potential issues, it's recommended to pass the inputs directly to CUDA using:
+```python
+inputs.input_ids.to('cuda')
+```
+
+We have released checkpoints for these models. For post-training, the naming convention is `step_XXXX`. 
+
+
+To load a specific model revision with HuggingFace, simply add the argument `revision`:
+```bash
+olmo = AutoModelForCausalLM.from_pretrained("allenai/Olmo-Hybrid-Instruct-SFT-7B", revision="step3000")
+```
+
+Or, you can access all the revisions for the models via the following code snippet:
+```python
+from huggingface_hub import list_repo_refs
+out = list_repo_refs("allenai/Olmo-Hybrid-Instruct-SFT-7B")
+branches = [b.name for b in out.branches]
+```
+
+### Chat template
+
+## Default System Message
+The default system prompt for this model is:
+```
+<|im_start|>system
+You are a helpful function-calling AI assistant. 
+You do not currently have access to any functions. <functions></functions><|im_end|>
+```
+
+## Chat Format
+
+The chat template for this model is formatted as:
+```
+<|im_start|>system
+You are a helpful function-calling AI assistant. 
+You do not currently have access to any functions. <functions></functions><|im_end|>
+<|im_start|>user
+Who would win in a fight - a dinosaur or a cow named Moo Moo?<|im_end|>
+<|im_start|>assistant
+This is a fun and imaginative question! Let’s break it down...
+Moo Moo the cow would certinaly win.
+<|endoftext|>
+```
+
+### Model Description
+
+- **Developed by:** Allen Institute for AI (Ai2)
+- **Model type:** a Transformer style autoregressive language model.
+- **Language(s) (NLP):** English
+- **License:** This model is licensed under Apache 2.0. It is intended for research and educational use in accordance with Ai2's [Responsible Use Guidelines](https://allenai.org/responsible-use).
+- **Contact:** Technical inquiries: `olmo@allenai.org`. Press: `press@allenai.org`
+- **Date cutoff:** Dec. 2024.
+
+
+### Model Sources
+
+- **Project Page:** https://allenai.org/olmo
+- **Repositories:**
+    - Open-Instruct for DPO and RLVR: https://github.com/allenai/open-instruct
+    - OLMo-Core for pre-training and SFT: https://github.com/allenai/OLMo-core
+    - OLMo-Eval for evaluation: https://github.com/allenai/OLMo-Eval
+- **Olmo 3 Paper:** https://allenai.org/papers/olmo3
+- **Olmo Hybrid Paper:** https://allenai.org/papers/olmo-hybrid
+
+## Evaluation
+
+| Skill | Benchmark | **Olmo Hybrid Instruct SFT 7B** | **Olmo Hybrid Instruct DPO 7B** | Olmo 3 Instruct 7B SFT | Olmo 3 Instruct 7B DPO | Olmo3 Instruct 7B | Qwen 3 8B (no reasoning) | Qwen 3 VL 8B Instruct | Qwen 2.5 7B | Olmo 2 7B Instruct | Apertus 8B Instruct | Granite 3.3 8B Instruct |
+|-------|-----------|--------------------------------|--------------------------------|------------------------|------------------------|-------------------|--------------------------|------------------------|-------------|-------------------|---------------------|------------------------|
+| Math | MATH | 66.7 | 72.9 | 65.1 | 79.6 | 87.3 | 82.3 | 91.6 | 71.0 | 30.1 | 21.9 | 67.3 |
+|  | AIME 2024 | 6.7 | 10.1 | 6.7 | 23.5 | 44.3 | 26.2 | 55.1 | 11.3 | 1.3 | 0.5 | 7.3 |
+|  | AIME 2025 | 8.8 | 10.2 | 7.2 | 20.4 | 32.5 | 21.7 | 43.3 | 6.3 | 0.4 | 0.2 | 6.3 |
+|  | OMEGA | 16.0 | 19.5 | 14.4 | 22.8 | 28.9 | 20.5 | 32.3 | 13.7 | 5.2 | 5.0 | 10.7 |
+| Reasoning | BigBenchHard | 47.3 | 57.3 | 51.0 | 69.3 | 71.2 | 73.7 | 85.6 | 68.8 | 43.8 | 42.2 | 61.2 |
+|  | ZebraLogic | 17.0 | 29.1 | 18.0 | 28.4 | 32.9 | 25.4 | 64.3 | 10.7 | 5.3 | 5.3 | 17.6 |
+|  | AGI Eval English | | | 59.2 | 64.0 | 64.4 | 76.0 | 84.5 | 69.8 | 56.1 | 50.8 | 64.0 |
+| Coding | HumanEvalPlus | 69.2 | 75.1 | 69.8 | 72.9 | 77.2 | 79.8 | 82.9 | 74.9 | 25.8 | 34.4 | 64.0 |
+|  | MBPP+ | 55.3 | 56.9 | 56.5 | 55.9 | 60.2 | 64.4 | 66.3 | 62.6 | 40.7 | 42.1 | 54.0 |
+|  | LiveCodeBench v3 | 21.3 | 22.0 | 20.0 | 18.8 | 29.5 | 53.2 | 55.9 | 34.5 | 7.2 | 7.8 | 11.5 |
+| IF | IFEval | 81.5 | 80.5 | 81.7 | 82.0 | 85.6 | 86.3 | 87.8 | 73.4 | 72.2 | 71.4 | 77.5 |
+|  | IFBench | 29.0 | 33.3 | 27.4 | 29.3 | 32.3 | 29.3 | 34.0 | 28.4 | 26.7 | 22.1 | 22.3 |
+| Knowledge | MMLU | 71.9 | 73.6 | 67.1 | 69.1 | 69.1 | 80.4 | 83.6 | 77.2 | 61.6 | 62.7 | 63.5 |
+| QA | PopQA | 16.8 | 21.0 | 16.5 | 20.7 | 14.1 | 20.4 | 26.5 | 21.5 | 25.5 | 25.5 | 28.9 |
+|  | GPQA | 36.8 | 38.0 | 30.0 | 37.9 | 40.4 | 44.6 | 51.1 | 35.6 | 31.3 | 28.8 | 33.0 |
+| Chat | AlpacaEval 2 LC | 25.6 | 56.3 | 21.8 | 43.3 | 40.9 | 49.8 | 73.5 | 23.0 | 18.3 | 8.1 | 28.6 |
+| Tool Use | SimpleQA | | | 74.2 | 79.8 | 79.3 | 79.0 | 90.3 | 78.0 | – | – | – |
+|  | LitQA2 | | | 38.0 | 43.3 | 38.2 | 39.6 | 30.7 | 29.8 | – | – | – |
+|  | BFCL | | | 48.9 | 49.6 | 49.8 | 60.2 | 66.2 | 55.8 | – | – | – |
+| Safety | Safety | | | 89.2 | 90.2 | 87.3 | 78.0 | 80.2 | 73.4 | 93.1 | 72.2 | 73.7 |
+
+## Model Details
+
+#### Stage 1: SFT
+- supervised fine-tuning on the Dolci-Instruct-SFT-7B dataset. This dataset consits of math, code, chat, and general knowledge queries.
+- Datasets: [Dolci-Instruct-SFT-7B](https://huggingface.co/datasets/allenai/dolci-instruct-sft)
+
+#### Stage 2:DPO
+- direct preference optimization on the Dolci-Instruct-DPO-7B dataset. This dataset consits of math, code, chat, and general knowledge queries.
+- Datasets: [Dolci-Instruct-DPO-7B](https://huggingface.co/datasets/allenai/dolci-3-instruct-dpo-with-metadata)
+
+## Inference & Recommended Settings
+We evaluated our models on the following settings. We also recommend using them for generation:
+- **temperature:** `0.6`
+- **top_p:** `0.95`
+- **max_tokens:** `32768`
+
+### transformers Example
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "allenai/Olmo-Hybrid-Instruct-SFT-7B"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    device_map="auto",
+)
+
+prompt = "Who would win in a fight - a dinosaur or a cow named MooMoo?"
+inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+
+outputs = model.generate(
+    **inputs,
+    temperature=0.6,
+    top_p=0.95,
+    max_new_tokens=32768,
+)
+
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+### vllm Example
+```python
+from vllm import LLM, SamplingParams
+
+model_id = "allenai/Olmo-Hybrid-Instruct-SFT-7B"
+llm = LLM(
+    model=model_id,
+    mamba_ssm_cache_dtype="float32",
+)
+
+sampling_params = SamplingParams(
+    temperature=0.6,
+    top_p=0.95,
+    max_tokens=32768,
+)
+
+prompt = "Who would win in a fight - a dinosaur or a cow named MooMoo?"
+outputs = llm.generate(prompt, sampling_params)
+print(outputs[0].outputs[0].text)
+```
+
+## Bias, Risks, and Limitations
+Like any base language model or fine-tuned model without safety filtering, these models can easily be prompted by users to generate harmful and sensitive content. Such content may also be produced unintentionally, especially in cases involving bias, so we recommend that users consider the risks when applying this technology. Additionally, many statements from OLMo or any LLM are often inaccurate, so facts should be verified.
+
+## License
+This model is licensed under Apache 2.0. It is intended for research and educational use in accordance with [Ai2's Responsible Use Guidelines](https://allenai.org/responsible-use).
+
+
+
+## Citation
+Coming Soon!
+
+## Model Card Contact
+For errors in this model card, contact `olmo@allenai.org`.

chat_template.jinja

@@ -0,0 +1,16 @@
+{%- set has_system = messages|selectattr('role', 'equalto', 'system')|list|length > 0 -%}{%- if not has_system -%}{{- '<|im_start|>system
+You are a helpful function-calling AI assistant. ' -}}{%- if tools is none or (tools | length) == 0 -%}{{- 'You do not currently have access to any functions. <functions></functions><|im_end|>
+' -}}{%- else -%}{{- 'You are provided with function signatures within <functions></functions> XML tags. You may call one or more functions to assist with the user query. Output any function calls within <function_calls></function_calls> XML tags. Do not make assumptions about what values to plug into functions.' -}}{{- '<functions>' -}}{{- tools | tojson -}}{{- '</functions><|im_end|>
+' -}}{%- endif -%}{%- endif -%}{%- for message in messages -%}{%- if message['role'] == 'system' -%}{{- '<|im_start|>system
+' + message['content'] -}}{%- if tools is not none -%}{{- '<functions>' -}}{{- tools | tojson -}}{{- '</functions>' -}}{%- elif message.get('functions', none) is not none -%}{{- ' <functions>' + message['functions'] + '</functions>' -}}{%- endif -%}{{- '<|im_end|>
+' -}}{%- elif message['role'] == 'user' -%}{{- '<|im_start|>user
+' + message['content'] + '<|im_end|>
+' -}}{%- elif message['role'] == 'assistant' -%}{{- '<|im_start|>assistant
+' -}}{%- if message.get('content', none) is not none -%}{{- message['content'] -}}{%- endif -%}{%- if message.get('function_calls', none) is not none and (message['function_calls'] | length) > 0 -%}{{- '<function_calls>' + message['function_calls'] + '</function_calls>' -}}{%- elif message.get('tool_calls', none) is not none and (message['tool_calls'] | length) > 0 -%}{{- '<function_calls>' -}}{%- for tool_call in message['tool_calls'] %}{%- if tool_call is mapping and tool_call.get('function', none) is not none %}{%- set args = tool_call['function']['arguments'] -%}{%- set ns = namespace(arguments_list=[]) -%}{%- for key, value in args.items() -%}{%- set ns.arguments_list = ns.arguments_list + [key ~ '=' ~ (value | tojson)] -%}{%- endfor -%}{%- set arguments = ns.arguments_list | join(', ') -%}{{- tool_call['function']['name'] + '(' + arguments + ')' -}}{%- if not loop.last -%}{{ '
+' }}{%- endif -%}{% else %}{{- tool_call -}}{%- endif %}{%- endfor %}{{- '</function_calls>' -}}{%- endif -%}{%- if not loop.last -%}{{- '<|im_end|>' + '
+' -}}{%- else -%}{{- eos_token -}}{%- endif -%}{%- elif message['role'] == 'environment' -%}{{- '<|im_start|>environment
+' + message['content'] + '<|im_end|>
+' -}}{%- elif message['role'] == 'tool' -%}{{- '<|im_start|>environment
+' + message['content'] + '<|im_end|>
+' -}}{%- endif -%}{%- if loop.last and add_generation_prompt -%}{{- '<|im_start|>assistant
+' -}}{%- endif -%}{%- endfor -%}

config.json

@@ -0,0 +1,77 @@
+{
+    "model_type": "olmo_hybrid",
+    "architectures": [
+        "OlmoHybridForCausalLM"
+    ],
+    "vocab_size": 100352,
+    "hidden_size": 3840,
+    "intermediate_size": 11008,
+    "num_hidden_layers": 32,
+    "num_attention_heads": 30,
+    "num_key_value_heads": 30,
+    "hidden_act": "silu",
+    "max_position_embeddings": 32768,
+    "initializer_range": 0.02,
+    "use_cache": true,
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "rms_norm_eps": 1e-06,
+    "tie_word_embeddings": false,
+    "layer_types": [
+        "linear_attention",
+        "linear_attention",
+        "linear_attention",
+        "full_attention",
+        "linear_attention",
+        "linear_attention",
+        "linear_attention",
+        "full_attention",
+        "linear_attention",
+        "linear_attention",
+        "linear_attention",
+        "full_attention",
+        "linear_attention",
+        "linear_attention",
+        "linear_attention",
+        "full_attention",
+        "linear_attention",
+        "linear_attention",
+        "linear_attention",
+        "full_attention",
+        "linear_attention",
+        "linear_attention",
+        "linear_attention",
+        "full_attention",
+        "linear_attention",
+        "linear_attention",
+        "linear_attention",
+        "full_attention",
+        "linear_attention",
+        "linear_attention",
+        "linear_attention",
+        "full_attention"
+    ],
+    "linear_num_key_heads": 30,
+    "linear_num_value_heads": 30,
+    "linear_key_head_dim": 96,
+    "linear_value_head_dim": 192,
+    "linear_conv_kernel_dim": 4,
+    "linear_allow_neg_eigval": true,
+    "pad_token_id": 100277,
+    "bos_token_id": null,
+    "eos_token_id": 100257,
+    "transformers_version": "4.52.0",
+    "rope_parameters": null,
+    "quantization_config": {
+        "quant_method": "exl3",
+        "version": "0.0.25",
+        "bits": 3.0,
+        "head_bits": 6,
+        "calibration": {
+            "rows": 250,
+            "cols": 2048
+        },
+        "out_scales": "always",
+        "codebook": "mcg"
+    }
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9e525d566f13ac323b72e5b4e880978a3f9c9fea2e719dcb44b8e93f52b5fbe9
+size 3573902085

special_tokens_map.json

@@ -0,0 +1,11 @@
+{
+  "eos_token": "<|endoftext|>",
+  "pad_token": "<|pad|>",
+  "unk_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

@@ -0,0 +1,189 @@
+{
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "100256": {
+      "content": "<|extra_id_0|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "100257": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100258": {
+      "content": "<|fim_prefix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100259": {
+      "content": "<|fim_middle|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100260": {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100261": {
+      "content": "|||PHONE_NUMBER|||",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "100262": {
+      "content": "|||EMAIL_ADDRESS|||",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "100263": {
+      "content": "|||IP_ADDRESS|||",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "100264": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100265": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100266": {
+      "content": "<functions>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "100267": {
+      "content": "</functions>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "100268": {
+      "content": "<function_calls>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "100269": {
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