Text Generation
Transformers
PyTorch
mistral
unsloth
trl
sft
conversational
text-generation-inference
Instructions to use MohamedSaeed-dev/phi-pycode with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MohamedSaeed-dev/phi-pycode with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="MohamedSaeed-dev/phi-pycode") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("MohamedSaeed-dev/phi-pycode") model = AutoModelForCausalLM.from_pretrained("MohamedSaeed-dev/phi-pycode") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use MohamedSaeed-dev/phi-pycode with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "MohamedSaeed-dev/phi-pycode" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "MohamedSaeed-dev/phi-pycode", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/MohamedSaeed-dev/phi-pycode
- SGLang
How to use MohamedSaeed-dev/phi-pycode 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 "MohamedSaeed-dev/phi-pycode" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "MohamedSaeed-dev/phi-pycode", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "MohamedSaeed-dev/phi-pycode" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "MohamedSaeed-dev/phi-pycode", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Unsloth Studio new
How to use MohamedSaeed-dev/phi-pycode 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 MohamedSaeed-dev/phi-pycode 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 MohamedSaeed-dev/phi-pycode to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for MohamedSaeed-dev/phi-pycode to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="MohamedSaeed-dev/phi-pycode", max_seq_length=2048, ) - Docker Model Runner
How to use MohamedSaeed-dev/phi-pycode with Docker Model Runner:
docker model run hf.co/MohamedSaeed-dev/phi-pycode
Upload tokenizer
Browse files- added_tokens.json +13 -0
- special_tokens_map.json +30 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +130 -0
added_tokens.json
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{
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"<|assistant|>": 32001,
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"<|endoftext|>": 32000,
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"<|end|>": 32007,
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"<|placeholder1|>": 32002,
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"<|placeholder2|>": 32003,
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"<|placeholder3|>": 32004,
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"<|placeholder4|>": 32005,
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"<|placeholder5|>": 32008,
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"<|placeholder6|>": 32009,
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"<|system|>": 32006,
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"<|user|>": 32010
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}
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special_tokens_map.json
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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": "<|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": "<|placeholder6|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": true,
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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.json
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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,
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"add_eos_token": false,
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"added_tokens_decoder": {
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"0": {
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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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"special": true
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},
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"1": {
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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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"special": true
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},
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"2": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": true,
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"single_word": false,
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"special": false
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},
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"32000": {
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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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"32001": {
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"content": "<|assistant|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": true,
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"single_word": false,
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"special": true
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},
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"32002": {
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"content": "<|placeholder1|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": true,
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"single_word": false,
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"special": true
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},
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"32003": {
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"content": "<|placeholder2|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": true,
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"single_word": false,
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"special": true
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},
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"32004": {
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"content": "<|placeholder3|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": true,
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"single_word": false,
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"special": true
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},
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"32005": {
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"content": "<|placeholder4|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": true,
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"single_word": false,
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"special": true
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},
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"32006": {
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"content": "<|system|>",
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| 79 |
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"lstrip": false,
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"normalized": false,
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"rstrip": true,
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"single_word": false,
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"special": true
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},
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"32007": {
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"content": "<|end|>",
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"lstrip": false,
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"normalized": false,
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| 89 |
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"rstrip": true,
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"single_word": false,
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"special": true
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},
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"32008": {
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"content": "<|placeholder5|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": true,
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"single_word": false,
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"special": true
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},
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"32009": {
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| 102 |
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"content": "<|placeholder6|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": true,
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"single_word": false,
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"special": true
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},
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"32010": {
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"content": "<|user|>",
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| 111 |
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"lstrip": false,
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| 112 |
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"normalized": false,
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| 113 |
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"rstrip": true,
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| 114 |
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"single_word": false,
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| 115 |
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"special": true
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}
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| 117 |
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},
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| 118 |
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"bos_token": "<s>",
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| 119 |
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"chat_template": "{{ bos_token }}{% for message in messages %}{% if message['from'] == 'human' %}{{'<|user|>\n' + message['value'] + '<|end|>\n'}}{% elif message['from'] == 'gpt' %}{{'<|assistant|>\n' + message['value'] + '<|end|>\n'}}{% else %}{{'<|' + message['from'] + '|>\n' + message['value'] + '<|end|>\n'}}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|assistant|>\n' }}{% endif %}",
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| 120 |
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"clean_up_tokenization_spaces": false,
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| 121 |
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"eos_token": "<|endoftext|>",
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| 122 |
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"legacy": false,
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| 123 |
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"model_max_length": 4096,
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| 124 |
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"pad_token": "<|placeholder6|>",
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| 125 |
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"padding_side": "left",
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| 126 |
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"sp_model_kwargs": {},
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| 127 |
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"tokenizer_class": "LlamaTokenizer",
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| 128 |
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"unk_token": "<unk>",
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| 129 |
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"use_default_system_prompt": false
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| 130 |
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}
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