Text Generation
Transformers
Safetensors
code
llama
react
javascript
typescript
python
code-review
deepseek
unsloth
lora
fine-tuned
conversational
text-generation-inference
Instructions to use nabinwell/deepseek-react-reviewer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nabinwell/deepseek-react-reviewer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="nabinwell/deepseek-react-reviewer") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("nabinwell/deepseek-react-reviewer") model = AutoModelForCausalLM.from_pretrained("nabinwell/deepseek-react-reviewer") 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 nabinwell/deepseek-react-reviewer with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "nabinwell/deepseek-react-reviewer" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "nabinwell/deepseek-react-reviewer", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/nabinwell/deepseek-react-reviewer
- SGLang
How to use nabinwell/deepseek-react-reviewer 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 "nabinwell/deepseek-react-reviewer" \ --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": "nabinwell/deepseek-react-reviewer", "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 "nabinwell/deepseek-react-reviewer" \ --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": "nabinwell/deepseek-react-reviewer", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Unsloth Studio new
How to use nabinwell/deepseek-react-reviewer 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 nabinwell/deepseek-react-reviewer 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 nabinwell/deepseek-react-reviewer to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for nabinwell/deepseek-react-reviewer to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="nabinwell/deepseek-react-reviewer", max_seq_length=2048, ) - Docker Model Runner
How to use nabinwell/deepseek-react-reviewer with Docker Model Runner:
docker model run hf.co/nabinwell/deepseek-react-reviewer
(Trained with Unsloth)
Browse files- chat_template.jinja +26 -0
- config.json +35 -0
- special_tokens_map.json +23 -0
- tokenizer.json +0 -0
- tokenizer_config.json +196 -0
chat_template.jinja
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{% if not add_generation_prompt is defined %}
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{% set add_generation_prompt = false %}
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{% endif %}
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{%- set ns = namespace(found=false) -%}
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{%- for message in messages -%}
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{%- if message['role'] == 'system' -%}
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{%- set ns.found = true -%}
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{%- endif -%}
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{%- endfor -%}
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{{bos_token}}{%- if not ns.found -%}
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{{'You are an AI programming assistant, utilizing the Deepseek Coder model, developed by Deepseek Company, and you only answer questions related to computer science. For politically sensitive questions, security and privacy issues, and other non-computer science questions, you will refuse to answer\n'}}
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{%- endif %}
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{%- for message in messages %}
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{%- if message['role'] == 'system' %}
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{{ message['content'] }}
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{%- else %}
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{%- if message['role'] == 'user' %}
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{{'### Instruction:\n' + message['content'] + '\n'}}
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{%- else %}
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{{'### Response:\n' + message['content'] + '\n<|EOT|>\n'}}
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{%- endif %}
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{%- endif %}
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{%- endfor %}
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{% if add_generation_prompt %}
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{{'### Response:'}}
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{% endif %}
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config.json
ADDED
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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": 32013,
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"torch_dtype": "float16",
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"eos_token_id": 32021,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 11008,
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"max_position_embeddings": 16384,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 32,
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"pad_token_id": 32014,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-06,
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"rope_scaling": {
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"factor": 4.0,
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"rope_type": "linear",
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"type": "linear"
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},
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"rope_theta": 100000,
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"tie_word_embeddings": false,
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"transformers_version": "4.57.6",
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"unsloth_version": "2026.1.4",
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"use_cache": true,
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"vocab_size": 32256
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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": "<|begin▁of▁sentence|>",
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"lstrip": false,
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"normalized": true,
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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": "<|EOT|>",
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"lstrip": false,
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"normalized": true,
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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": "<|end▁of▁sentence|>",
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"lstrip": false,
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"normalized": true,
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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
ADDED
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The diff for this file is too large to render.
See raw diff
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tokenizer_config.json
ADDED
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{
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| 2 |
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"add_bos_token": true,
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| 3 |
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"add_eos_token": false,
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| 4 |
+
"add_prefix_space": null,
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| 5 |
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"added_tokens_decoder": {
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| 6 |
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"32000": {
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| 7 |
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"content": "õ",
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| 8 |
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"lstrip": false,
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| 9 |
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"normalized": true,
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| 10 |
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"rstrip": false,
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| 11 |
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"single_word": false,
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| 12 |
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"special": false
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| 13 |
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},
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| 14 |
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"32001": {
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| 15 |
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"content": "÷",
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| 16 |
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"lstrip": false,
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| 17 |
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"normalized": true,
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| 18 |
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"rstrip": false,
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| 19 |
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"single_word": false,
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| 20 |
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"special": false
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},
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| 22 |
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"32002": {
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| 23 |
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"content": "Á",
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| 24 |
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"lstrip": false,
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| 25 |
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"normalized": true,
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| 26 |
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"rstrip": false,
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| 27 |
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"single_word": false,
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| 28 |
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"special": false
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| 29 |
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},
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| 30 |
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"32003": {
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| 31 |
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"content": "ý",
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| 32 |
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"lstrip": false,
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| 33 |
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"normalized": true,
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| 34 |
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"rstrip": false,
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| 35 |
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"single_word": false,
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| 36 |
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"special": false
|
| 37 |
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},
|
| 38 |
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"32004": {
|
| 39 |
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"content": "À",
|
| 40 |
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"lstrip": false,
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| 41 |
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"normalized": true,
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| 42 |
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"rstrip": false,
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| 43 |
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"single_word": false,
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| 44 |
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"special": false
|
| 45 |
+
},
|
| 46 |
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"32005": {
|
| 47 |
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"content": "ÿ",
|
| 48 |
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"lstrip": false,
|
| 49 |
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"normalized": true,
|
| 50 |
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"rstrip": false,
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| 51 |
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"single_word": false,
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| 52 |
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"special": false
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| 53 |
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},
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| 54 |
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"32006": {
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| 55 |
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"content": "ø",
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| 56 |
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"lstrip": false,
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| 57 |
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"normalized": true,
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| 58 |
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"rstrip": false,
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| 59 |
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"single_word": false,
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| 60 |
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"special": false
|
| 61 |
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},
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| 62 |
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"32007": {
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| 63 |
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"content": "ú",
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| 64 |
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"lstrip": false,
|
| 65 |
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"normalized": true,
|
| 66 |
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"rstrip": false,
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| 67 |
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"single_word": false,
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| 68 |
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"special": false
|
| 69 |
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},
|
| 70 |
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"32008": {
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| 71 |
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"content": "þ",
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| 72 |
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"lstrip": false,
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| 73 |
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"normalized": true,
|
| 74 |
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"rstrip": false,
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| 75 |
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"single_word": false,
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| 76 |
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"special": false
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| 77 |
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},
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| 78 |
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"32009": {
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| 79 |
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"content": "ü",
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| 80 |
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"lstrip": false,
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| 81 |
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"normalized": true,
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| 82 |
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"rstrip": false,
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| 83 |
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"single_word": false,
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| 84 |
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"special": false
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| 85 |
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},
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| 86 |
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"32010": {
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| 87 |
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"content": "ù",
|
| 88 |
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"lstrip": false,
|
| 89 |
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"normalized": true,
|
| 90 |
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"rstrip": false,
|
| 91 |
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"single_word": false,
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| 92 |
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"special": false
|
| 93 |
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},
|
| 94 |
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"32011": {
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| 95 |
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"content": "ö",
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| 96 |
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"lstrip": false,
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| 97 |
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"normalized": true,
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| 98 |
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"rstrip": false,
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| 99 |
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"single_word": false,
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| 100 |
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"special": false
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| 101 |
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},
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| 102 |
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"32012": {
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| 103 |
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"content": "û",
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| 104 |
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"lstrip": false,
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| 105 |
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"normalized": true,
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| 106 |
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"rstrip": false,
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| 107 |
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"single_word": false,
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| 108 |
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"special": false
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| 109 |
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},
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| 110 |
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"32013": {
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| 111 |
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"content": "<|begin▁of▁sentence|>",
|
| 112 |
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"lstrip": false,
|
| 113 |
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"normalized": true,
|
| 114 |
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"rstrip": false,
|
| 115 |
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"single_word": false,
|
| 116 |
+
"special": true
|
| 117 |
+
},
|
| 118 |
+
"32014": {
|
| 119 |
+
"content": "<|end▁of▁sentence|>",
|
| 120 |
+
"lstrip": false,
|
| 121 |
+
"normalized": true,
|
| 122 |
+
"rstrip": false,
|
| 123 |
+
"single_word": false,
|
| 124 |
+
"special": true
|
| 125 |
+
},
|
| 126 |
+
"32015": {
|
| 127 |
+
"content": "<|fim▁hole|>",
|
| 128 |
+
"lstrip": false,
|
| 129 |
+
"normalized": true,
|
| 130 |
+
"rstrip": false,
|
| 131 |
+
"single_word": false,
|
| 132 |
+
"special": false
|
| 133 |
+
},
|
| 134 |
+
"32016": {
|
| 135 |
+
"content": "<|fim▁begin|>",
|
| 136 |
+
"lstrip": false,
|
| 137 |
+
"normalized": true,
|
| 138 |
+
"rstrip": false,
|
| 139 |
+
"single_word": false,
|
| 140 |
+
"special": false
|
| 141 |
+
},
|
| 142 |
+
"32017": {
|
| 143 |
+
"content": "<|fim▁end|>",
|
| 144 |
+
"lstrip": false,
|
| 145 |
+
"normalized": true,
|
| 146 |
+
"rstrip": false,
|
| 147 |
+
"single_word": false,
|
| 148 |
+
"special": false
|
| 149 |
+
},
|
| 150 |
+
"32018": {
|
| 151 |
+
"content": "<pad>",
|
| 152 |
+
"lstrip": false,
|
| 153 |
+
"normalized": true,
|
| 154 |
+
"rstrip": false,
|
| 155 |
+
"single_word": false,
|
| 156 |
+
"special": false
|
| 157 |
+
},
|
| 158 |
+
"32019": {
|
| 159 |
+
"content": "<|User|>",
|
| 160 |
+
"lstrip": false,
|
| 161 |
+
"normalized": true,
|
| 162 |
+
"rstrip": false,
|
| 163 |
+
"single_word": false,
|
| 164 |
+
"special": false
|
| 165 |
+
},
|
| 166 |
+
"32020": {
|
| 167 |
+
"content": "<|Assistant|>",
|
| 168 |
+
"lstrip": false,
|
| 169 |
+
"normalized": true,
|
| 170 |
+
"rstrip": false,
|
| 171 |
+
"single_word": false,
|
| 172 |
+
"special": false
|
| 173 |
+
},
|
| 174 |
+
"32021": {
|
| 175 |
+
"content": "<|EOT|>",
|
| 176 |
+
"lstrip": false,
|
| 177 |
+
"normalized": true,
|
| 178 |
+
"rstrip": false,
|
| 179 |
+
"single_word": false,
|
| 180 |
+
"special": true
|
| 181 |
+
}
|
| 182 |
+
},
|
| 183 |
+
"bos_token": "<|begin▁of▁sentence|>",
|
| 184 |
+
"clean_up_tokenization_spaces": false,
|
| 185 |
+
"eos_token": "<|EOT|>",
|
| 186 |
+
"extra_special_tokens": {},
|
| 187 |
+
"legacy": true,
|
| 188 |
+
"model_max_length": 16384,
|
| 189 |
+
"pad_token": "<|end▁of▁sentence|>",
|
| 190 |
+
"padding_side": "left",
|
| 191 |
+
"sp_model_kwargs": {},
|
| 192 |
+
"tokenizer_class": "LlamaTokenizerFast",
|
| 193 |
+
"unk_token": null,
|
| 194 |
+
"use_default_system_prompt": false,
|
| 195 |
+
"chat_template": "{% if not add_generation_prompt is defined %}\n{% set add_generation_prompt = false %}\n{% endif %}\n{%- set ns = namespace(found=false) -%}\n{%- for message in messages -%}\n {%- if message['role'] == 'system' -%}\n {%- set ns.found = true -%}\n {%- endif -%}\n{%- endfor -%}\n{{bos_token}}{%- if not ns.found -%}\n{{'You are an AI programming assistant, utilizing the Deepseek Coder model, developed by Deepseek Company, and you only answer questions related to computer science. For politically sensitive questions, security and privacy issues, and other non-computer science questions, you will refuse to answer\\n'}}\n{%- endif %}\n{%- for message in messages %}\n {%- if message['role'] == 'system' %}\n{{ message['content'] }}\n {%- else %}\n {%- if message['role'] == 'user' %}\n{{'### Instruction:\\n' + message['content'] + '\\n'}}\n {%- else %}\n{{'### Response:\\n' + message['content'] + '\\n<|EOT|>\\n'}}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{% if add_generation_prompt %}\n{{'### Response:'}}\n{% endif %}"
|
| 196 |
+
}
|