Instructions to use KBlueLeaf/TIPO-500M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KBlueLeaf/TIPO-500M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="KBlueLeaf/TIPO-500M")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("KBlueLeaf/TIPO-500M") model = AutoModelForCausalLM.from_pretrained("KBlueLeaf/TIPO-500M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use KBlueLeaf/TIPO-500M with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf KBlueLeaf/TIPO-500M:F16 # Run inference directly in the terminal: llama cli -hf KBlueLeaf/TIPO-500M:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf KBlueLeaf/TIPO-500M:F16 # Run inference directly in the terminal: llama cli -hf KBlueLeaf/TIPO-500M:F16
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf KBlueLeaf/TIPO-500M:F16 # Run inference directly in the terminal: ./llama-cli -hf KBlueLeaf/TIPO-500M:F16
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf KBlueLeaf/TIPO-500M:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf KBlueLeaf/TIPO-500M:F16
Use Docker
docker model run hf.co/KBlueLeaf/TIPO-500M:F16
- LM Studio
- Jan
- vLLM
How to use KBlueLeaf/TIPO-500M with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "KBlueLeaf/TIPO-500M" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "KBlueLeaf/TIPO-500M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/KBlueLeaf/TIPO-500M:F16
- SGLang
How to use KBlueLeaf/TIPO-500M with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "KBlueLeaf/TIPO-500M" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "KBlueLeaf/TIPO-500M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "KBlueLeaf/TIPO-500M" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "KBlueLeaf/TIPO-500M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Ollama
How to use KBlueLeaf/TIPO-500M with Ollama:
ollama run hf.co/KBlueLeaf/TIPO-500M:F16
- Unsloth Desktop
- Docker Model Runner
How to use KBlueLeaf/TIPO-500M with Docker Model Runner:
docker model run hf.co/KBlueLeaf/TIPO-500M:F16
- Lemonade
How to use KBlueLeaf/TIPO-500M with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull KBlueLeaf/TIPO-500M:F16
Run and chat with the model
lemonade run user.TIPO-500M-F16
List all available models
lemonade list
- Atomic Chat
Upload 8 files
Browse files- .gitattributes +1 -0
- TIPO-500M_epoch5-F16.gguf +3 -0
- added_tokens.json +15 -0
- config.json +30 -0
- generation_config.json +8 -0
- model.safetensors +3 -0
- special_tokens_map.json +45 -0
- tokenizer.model +3 -0
- tokenizer_config.json +162 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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TIPO-500M_epoch5-F16.gguf filter=lfs diff=lfs merge=lfs -text
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TIPO-500M_epoch5-F16.gguf
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version https://git-lfs.github.com/spec/v1
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added_tokens.json
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{
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"<|empty|>": 32000,
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"<|gen_meta|>": 32012,
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"<|long|>": 32003,
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"<|short_to_long_to_tag|>": 32011,
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"<|short_to_long|>": 32008,
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"<|short_to_tag_to_long|>": 32010,
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"<|short_to_tag|>": 32007,
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"<|short|>": 32002,
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"<|tag_to_long|>": 32005,
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"<|tag_to_short_to_long|>": 32009,
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"<|very_long|>": 32004,
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"<|very_short|>": 32001
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}
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config.json
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{
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"_name_or_path": "./config/arch/NanoLLaMA-500m.json",
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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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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 1280,
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"initializer_range": 0.02,
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"intermediate_size": 3840,
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"max_position_embeddings": 2048,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 20,
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"num_hidden_layers": 20,
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"num_key_value_heads": 20,
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"pad_token_id": 2,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 10000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "float32",
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"transformers_version": "4.44.2",
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"use_cache": false,
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"vocab_size": 32013
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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": "4.44.2",
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"use_cache": false
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:cfa6063be163426a0a15a0b183631855f97df30169703ae05349c8c63a587c1f
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size 2031979904
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special_tokens_map.json
ADDED
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{
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"additional_special_tokens": [
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"<|empty|>",
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"<|very_short|>",
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"<|short|>",
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"<|long|>",
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"<|very_long|>",
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"<|tag_to_long|>",
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"<|long_to_tag|>",
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"<|short_to_tag|>",
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"<|short_to_long|>",
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"<|tag_to_short_to_long|>",
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"<|short_to_tag_to_long|>",
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"<|short_to_long_to_tag|>",
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"<|gen_meta|>"
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],
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"bos_token": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
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size 499723
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tokenizer_config.json
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{
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"add_bos_token": true,
|
| 3 |
+
"add_eos_token": false,
|
| 4 |
+
"add_prefix_space": true,
|
| 5 |
+
"added_tokens_decoder": {
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| 6 |
+
"0": {
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| 7 |
+
"content": "<unk>",
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| 8 |
+
"lstrip": false,
|
| 9 |
+
"normalized": false,
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| 10 |
+
"rstrip": false,
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| 11 |
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"single_word": false,
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| 12 |
+
"special": true
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| 13 |
+
},
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| 14 |
+
"1": {
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| 15 |
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"content": "<s>",
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| 16 |
+
"lstrip": false,
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| 17 |
+
"normalized": false,
|
| 18 |
+
"rstrip": false,
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| 19 |
+
"single_word": false,
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| 20 |
+
"special": true
|
| 21 |
+
},
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| 22 |
+
"2": {
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| 23 |
+
"content": "</s>",
|
| 24 |
+
"lstrip": false,
|
| 25 |
+
"normalized": false,
|
| 26 |
+
"rstrip": false,
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| 27 |
+
"single_word": false,
|
| 28 |
+
"special": true
|
| 29 |
+
},
|
| 30 |
+
"32000": {
|
| 31 |
+
"content": "<|empty|>",
|
| 32 |
+
"lstrip": false,
|
| 33 |
+
"normalized": false,
|
| 34 |
+
"rstrip": false,
|
| 35 |
+
"single_word": false,
|
| 36 |
+
"special": true
|
| 37 |
+
},
|
| 38 |
+
"32001": {
|
| 39 |
+
"content": "<|very_short|>",
|
| 40 |
+
"lstrip": false,
|
| 41 |
+
"normalized": false,
|
| 42 |
+
"rstrip": false,
|
| 43 |
+
"single_word": false,
|
| 44 |
+
"special": true
|
| 45 |
+
},
|
| 46 |
+
"32002": {
|
| 47 |
+
"content": "<|short|>",
|
| 48 |
+
"lstrip": false,
|
| 49 |
+
"normalized": false,
|
| 50 |
+
"rstrip": false,
|
| 51 |
+
"single_word": false,
|
| 52 |
+
"special": true
|
| 53 |
+
},
|
| 54 |
+
"32003": {
|
| 55 |
+
"content": "<|long|>",
|
| 56 |
+
"lstrip": false,
|
| 57 |
+
"normalized": false,
|
| 58 |
+
"rstrip": false,
|
| 59 |
+
"single_word": false,
|
| 60 |
+
"special": true
|
| 61 |
+
},
|
| 62 |
+
"32004": {
|
| 63 |
+
"content": "<|very_long|>",
|
| 64 |
+
"lstrip": false,
|
| 65 |
+
"normalized": false,
|
| 66 |
+
"rstrip": false,
|
| 67 |
+
"single_word": false,
|
| 68 |
+
"special": true
|
| 69 |
+
},
|
| 70 |
+
"32005": {
|
| 71 |
+
"content": "<|tag_to_long|>",
|
| 72 |
+
"lstrip": false,
|
| 73 |
+
"normalized": false,
|
| 74 |
+
"rstrip": false,
|
| 75 |
+
"single_word": false,
|
| 76 |
+
"special": true
|
| 77 |
+
},
|
| 78 |
+
"32006": {
|
| 79 |
+
"content": "<|long_to_tag|>",
|
| 80 |
+
"lstrip": false,
|
| 81 |
+
"normalized": false,
|
| 82 |
+
"rstrip": false,
|
| 83 |
+
"single_word": false,
|
| 84 |
+
"special": true
|
| 85 |
+
},
|
| 86 |
+
"32007": {
|
| 87 |
+
"content": "<|short_to_tag|>",
|
| 88 |
+
"lstrip": false,
|
| 89 |
+
"normalized": false,
|
| 90 |
+
"rstrip": false,
|
| 91 |
+
"single_word": false,
|
| 92 |
+
"special": true
|
| 93 |
+
},
|
| 94 |
+
"32008": {
|
| 95 |
+
"content": "<|short_to_long|>",
|
| 96 |
+
"lstrip": false,
|
| 97 |
+
"normalized": false,
|
| 98 |
+
"rstrip": false,
|
| 99 |
+
"single_word": false,
|
| 100 |
+
"special": true
|
| 101 |
+
},
|
| 102 |
+
"32009": {
|
| 103 |
+
"content": "<|tag_to_short_to_long|>",
|
| 104 |
+
"lstrip": false,
|
| 105 |
+
"normalized": false,
|
| 106 |
+
"rstrip": false,
|
| 107 |
+
"single_word": false,
|
| 108 |
+
"special": true
|
| 109 |
+
},
|
| 110 |
+
"32010": {
|
| 111 |
+
"content": "<|short_to_tag_to_long|>",
|
| 112 |
+
"lstrip": false,
|
| 113 |
+
"normalized": false,
|
| 114 |
+
"rstrip": false,
|
| 115 |
+
"single_word": false,
|
| 116 |
+
"special": true
|
| 117 |
+
},
|
| 118 |
+
"32011": {
|
| 119 |
+
"content": "<|short_to_long_to_tag|>",
|
| 120 |
+
"lstrip": false,
|
| 121 |
+
"normalized": false,
|
| 122 |
+
"rstrip": false,
|
| 123 |
+
"single_word": false,
|
| 124 |
+
"special": true
|
| 125 |
+
},
|
| 126 |
+
"32012": {
|
| 127 |
+
"content": "<|gen_meta|>",
|
| 128 |
+
"lstrip": false,
|
| 129 |
+
"normalized": false,
|
| 130 |
+
"rstrip": false,
|
| 131 |
+
"single_word": false,
|
| 132 |
+
"special": true
|
| 133 |
+
}
|
| 134 |
+
},
|
| 135 |
+
"additional_special_tokens": [
|
| 136 |
+
"<|empty|>",
|
| 137 |
+
"<|very_short|>",
|
| 138 |
+
"<|short|>",
|
| 139 |
+
"<|long|>",
|
| 140 |
+
"<|very_long|>",
|
| 141 |
+
"<|tag_to_long|>",
|
| 142 |
+
"<|long_to_tag|>",
|
| 143 |
+
"<|short_to_tag|>",
|
| 144 |
+
"<|short_to_long|>",
|
| 145 |
+
"<|tag_to_short_to_long|>",
|
| 146 |
+
"<|short_to_tag_to_long|>",
|
| 147 |
+
"<|short_to_long_to_tag|>",
|
| 148 |
+
"<|gen_meta|>"
|
| 149 |
+
],
|
| 150 |
+
"bos_token": "<s>",
|
| 151 |
+
"clean_up_tokenization_spaces": false,
|
| 152 |
+
"eos_token": "</s>",
|
| 153 |
+
"legacy": false,
|
| 154 |
+
"model_max_length": 1000000000000000019884624838656,
|
| 155 |
+
"pad_token": "</s>",
|
| 156 |
+
"padding_side": "right",
|
| 157 |
+
"sp_model_kwargs": {},
|
| 158 |
+
"spaces_between_special_tokens": false,
|
| 159 |
+
"tokenizer_class": "LlamaTokenizer",
|
| 160 |
+
"unk_token": "<unk>",
|
| 161 |
+
"use_default_system_prompt": false
|
| 162 |
+
}
|