Instructions to use fevohh/RayExtract-360M-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use fevohh/RayExtract-360M-v1 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="fevohh/RayExtract-360M-v1", filename="unsloth.F16.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use fevohh/RayExtract-360M-v1 with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf fevohh/RayExtract-360M-v1:Q4_K_M # Run inference directly in the terminal: llama-cli -hf fevohh/RayExtract-360M-v1:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf fevohh/RayExtract-360M-v1:Q4_K_M # Run inference directly in the terminal: llama-cli -hf fevohh/RayExtract-360M-v1:Q4_K_M
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 fevohh/RayExtract-360M-v1:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf fevohh/RayExtract-360M-v1:Q4_K_M
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 fevohh/RayExtract-360M-v1:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf fevohh/RayExtract-360M-v1:Q4_K_M
Use Docker
docker model run hf.co/fevohh/RayExtract-360M-v1:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use fevohh/RayExtract-360M-v1 with Ollama:
ollama run hf.co/fevohh/RayExtract-360M-v1:Q4_K_M
- Unsloth Studio new
How to use fevohh/RayExtract-360M-v1 with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for fevohh/RayExtract-360M-v1 to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for fevohh/RayExtract-360M-v1 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for fevohh/RayExtract-360M-v1 to start chatting
- Docker Model Runner
How to use fevohh/RayExtract-360M-v1 with Docker Model Runner:
docker model run hf.co/fevohh/RayExtract-360M-v1:Q4_K_M
- Lemonade
How to use fevohh/RayExtract-360M-v1 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull fevohh/RayExtract-360M-v1:Q4_K_M
Run and chat with the model
lemonade run user.RayExtract-360M-v1-Q4_K_M
List all available models
lemonade list
Upload model trained with Unsloth
Browse filesUpload model trained with Unsloth 2x faster
- added_tokens.json +3 -0
- merges.txt +0 -0
- special_tokens_map.json +43 -0
- tokenizer.json +0 -0
- tokenizer_config.json +186 -0
- vocab.json +0 -0
added_tokens.json
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{
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"<|PAD_TOKEN|>": 49152
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}
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merges.txt
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special_tokens_map.json
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{
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"additional_special_tokens": [
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"<|endoftext|>",
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"<|im_start|>",
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"<|im_end|>",
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"<repo_name>",
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"<reponame>",
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"<file_sep>",
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"<filename>",
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"<gh_stars>",
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"<issue_start>",
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"<issue_comment>",
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"<issue_closed>",
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"<jupyter_start>",
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"<jupyter_text>",
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"<jupyter_code>",
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"<jupyter_output>",
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"<jupyter_script>",
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"<empty_output>"
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],
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"bos_token": {
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"content": "<|endoftext|>",
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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": "<|endoftext|>",
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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": "<|PAD_TOKEN|>",
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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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}
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tokenizer.json
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tokenizer_config.json
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{
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"add_prefix_space": false,
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"added_tokens_decoder": {
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"0": {
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"content": "<|endoftext|>",
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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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"special": true
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},
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"1": {
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"content": "<|im_start|>",
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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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"special": true
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},
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"2": {
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"content": "<|im_end|>",
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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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"special": true
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},
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"3": {
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"content": "<repo_name>",
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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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"special": true
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},
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"4": {
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"content": "<reponame>",
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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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"special": true
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},
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"5": {
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"content": "<file_sep>",
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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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"special": true
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},
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"6": {
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"content": "<filename>",
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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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"special": true
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},
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"7": {
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"content": "<gh_stars>",
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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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"special": true
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},
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"8": {
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"content": "<issue_start>",
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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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"special": true
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},
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"9": {
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"content": "<issue_comment>",
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"lstrip": false,
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| 79 |
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"normalized": false,
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| 80 |
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"rstrip": false,
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| 81 |
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"single_word": false,
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"special": true
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},
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"10": {
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"content": "<issue_closed>",
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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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"special": true
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},
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"11": {
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"content": "<jupyter_start>",
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| 94 |
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"lstrip": false,
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| 95 |
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"normalized": false,
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| 96 |
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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| 100 |
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"12": {
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"content": "<jupyter_text>",
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| 102 |
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"lstrip": false,
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"normalized": false,
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| 104 |
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"rstrip": false,
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"single_word": false,
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| 106 |
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"special": true
|
| 107 |
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},
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| 108 |
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"13": {
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| 109 |
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"content": "<jupyter_code>",
|
| 110 |
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"lstrip": false,
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| 111 |
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"normalized": false,
|
| 112 |
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"rstrip": false,
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"single_word": false,
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| 114 |
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"special": true
|
| 115 |
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},
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"14": {
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"content": "<jupyter_output>",
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"lstrip": false,
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| 119 |
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"normalized": false,
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| 120 |
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"rstrip": false,
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| 121 |
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"single_word": false,
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| 122 |
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"special": true
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| 123 |
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},
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"15": {
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| 125 |
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"content": "<jupyter_script>",
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| 126 |
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"lstrip": false,
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"normalized": false,
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| 128 |
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"rstrip": false,
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| 129 |
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"single_word": false,
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"special": true
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| 131 |
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},
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| 132 |
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"16": {
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| 133 |
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"content": "<empty_output>",
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| 134 |
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"lstrip": false,
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| 135 |
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"normalized": false,
|
| 136 |
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"rstrip": false,
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| 137 |
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"single_word": false,
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| 138 |
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"special": true
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| 139 |
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},
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| 140 |
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"24211": {
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| 141 |
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"content": "�",
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| 142 |
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"lstrip": false,
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| 143 |
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"normalized": false,
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| 144 |
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"rstrip": false,
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| 145 |
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"single_word": false,
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| 146 |
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"special": true
|
| 147 |
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},
|
| 148 |
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"49152": {
|
| 149 |
+
"content": "<|PAD_TOKEN|>",
|
| 150 |
+
"lstrip": false,
|
| 151 |
+
"normalized": false,
|
| 152 |
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"rstrip": false,
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| 153 |
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"single_word": false,
|
| 154 |
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"special": true
|
| 155 |
+
}
|
| 156 |
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},
|
| 157 |
+
"additional_special_tokens": [
|
| 158 |
+
"<|endoftext|>",
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| 159 |
+
"<|im_start|>",
|
| 160 |
+
"<|im_end|>",
|
| 161 |
+
"<repo_name>",
|
| 162 |
+
"<reponame>",
|
| 163 |
+
"<file_sep>",
|
| 164 |
+
"<filename>",
|
| 165 |
+
"<gh_stars>",
|
| 166 |
+
"<issue_start>",
|
| 167 |
+
"<issue_comment>",
|
| 168 |
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"<issue_closed>",
|
| 169 |
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"<jupyter_start>",
|
| 170 |
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"<jupyter_text>",
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| 171 |
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"<jupyter_code>",
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| 172 |
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"<jupyter_output>",
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| 173 |
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"<jupyter_script>",
|
| 174 |
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"<empty_output>"
|
| 175 |
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],
|
| 176 |
+
"bos_token": "<|endoftext|>",
|
| 177 |
+
"clean_up_tokenization_spaces": false,
|
| 178 |
+
"eos_token": "<|endoftext|>",
|
| 179 |
+
"extra_special_tokens": {},
|
| 180 |
+
"model_max_length": 8192,
|
| 181 |
+
"pad_token": "<|PAD_TOKEN|>",
|
| 182 |
+
"padding_side": "right",
|
| 183 |
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"tokenizer_class": "GPT2Tokenizer",
|
| 184 |
+
"unk_token": "�",
|
| 185 |
+
"vocab_size": 49152
|
| 186 |
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}
|
vocab.json
ADDED
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