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Model: artindnr/tea Source: Original Platform
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README.md
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---
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license: mit
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base_model: microsoft/phi-4
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tags:
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- fine-tuned
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- full-fine-tune
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- text-generation
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- chat
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- question-answering
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- assistant
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- pytorch
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language:
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- fa
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- en
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- multilingual
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pipeline_tag: text-generation
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---
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# 🍵 Tea
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**Tea** is a full fine-tune of [`microsoft/phi-4`](https://huggingface.co/microsoft/phi-4), built for **question answering and long, sustained assistant-style conversations**. It is multilingual, with fine-tuning focused on strong, natural **Farsi (Persian)** conversational ability, while retaining Phi-4's general English and multilingual competence.
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## Model Details
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- **Base model:** [microsoft/phi-4](https://huggingface.co/microsoft/phi-4) (14B parameters)
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- **Fine-tuning method:** Full fine-tune — all parameters updated, no LoRA/PEFT adapters
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- **Fine-tuned by:** [artindnr](https://huggingface.co/artindnr)
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- **License:** MIT
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- **Languages:** Farsi (primary conversational focus), English, and general multilingual support
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- **Model type:** Causal decoder-only chat/assistant language model
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## What's New
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tea takes Phi-4's strong base reasoning and language capabilities and tunes them specifically for:
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- **Question answering** — direct, accurate answers grounded in the conversation context
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- **Long assistant conversations** — maintaining coherence, tone, and context over extended multi-turn sessions rather than short single-shot exchanges
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- **Farsi fluency** — natural, idiomatic Persian conversation and assistance, alongside solid English and multilingual performance
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Unlike adapter-based fine-tunes, every weight in the model was updated during training, which the author has found gives more consistent behavior for long-conversation use cases than LoRA-based approaches.
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## How to Use
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Tea uses the standard chat template shipped with the base model, so it works out of the box with 🤗 Transformers.
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### Generation
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```python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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MODEL_ID = "artindnr/tea"
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tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
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model = AutoModelForCausalLM.from_pretrained(
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MODEL_ID,
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torch_dtype=torch.bfloat16,
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device_map="auto",
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)
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USER_PROMPT = "تو کی هستی و اسمت چیه؟"
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messages = [
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{"role": "user", "content": USER_PROMPT},
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]
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inputs = tokenizer.apply_chat_template(
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messages,
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add_generation_prompt=True,
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tokenize=True,
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return_dict=True,
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return_tensors="pt",
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).to(model.device)
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outputs = model.generate(
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**inputs,
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max_new_tokens=1024,
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temperature=0.7,
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do_sample=True,
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)
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print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:], skip_special_tokens=True))
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```
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For multi-turn conversations, simply keep appending `{"role": "user", ...}` / `{"role": "assistant", ...}` turns to the `messages` list before re-applying the chat template — tea is tuned to stay coherent as this history grows.
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## Intended Use
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tea is intended for:
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- Farsi-first conversational assistants that also need to handle English/multilingual input
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- Question-answering applications requiring direct, grounded answers
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- Long-running, multi-turn assistant deployments (support bots, tutoring, general-purpose chat) where conversational memory and coherence over many turns matters
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- Research comparing full fine-tunes vs. adapter-based (LoRA) fine-tunes on the same base model
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## Limitations
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- As a full fine-tune, tea's Farsi-focused training may shift some of Phi-4's original English-centric behaviors; for English-only, general-purpose use cases the base `microsoft/phi-4` model may still be preferable.
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- tea inherits the general capabilities and limitations of the `phi-4` base model, including the possibility of hallucinated facts, especially over very long contexts.
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- No formal safety fine-tuning beyond what is inherited from the base model has been applied; use appropriate safeguards in production settings.
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## License
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This model is released under the [MIT License](https://opensource.org/licenses/MIT), consistent with the base `microsoft/phi-4` model.
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## Citation
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If you use tea in your work, please cite:
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```bibtex
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@misc{tea,
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title = {tea: A Farsi-Focused, Full Fine-tune of Phi-4 for QA and Long-form Assistance},
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author = {artindnr},
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year = {2026},
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url = {https://huggingface.co/artindnr/tea}
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}
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```
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## Acknowledgements
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Built on top of [`microsoft/phi-4`](https://huggingface.co/microsoft/phi-4).
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chat_template.jinja
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{% for message in messages %}{% if (message['role'] == 'system') %}{{'<|im_start|>system<|im_sep|>' + message['content'] + '<|im_end|>'}}{% elif (message['role'] == 'user') %}{{'<|im_start|>user<|im_sep|>' + message['content'] + '<|im_end|>'}}{% elif (message['role'] == 'assistant') %}{{'<|im_start|>assistant<|im_sep|>' + message['content'] + '<|im_end|>'}}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant<|im_sep|>' }}{% endif %}
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config.json
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config.json
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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": 100257,
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"torch_dtype": "bfloat16",
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"eos_token_id": 100265,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 5120,
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"initializer_range": 0.02,
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"intermediate_size": 17920,
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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": 40,
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"num_hidden_layers": 40,
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"num_key_value_heads": 10,
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"original_max_position_embeddings": 16384,
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"pad_token_id": 100351,
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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": 250000,
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"tie_word_embeddings": false,
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"unsloth_fixed": true,
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"unsloth_version": "2026.8.8",
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"use_cache": true,
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"vocab_size": 100352
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}
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||||
}
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||||
30
special_tokens_map.json
Normal file
30
special_tokens_map.json
Normal file
@@ -0,0 +1,30 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<|endoftext|>",
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||||
"lstrip": true,
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||||
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|
||||
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||||
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|
||||
},
|
||||
"eos_token": {
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||||
"content": "<|im_end|>",
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||||
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||||
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|
||||
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|
||||
"single_word": false
|
||||
},
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||||
"pad_token": {
|
||||
"content": "<|dummy_87|>",
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||||
"lstrip": true,
|
||||
"normalized": false,
|
||||
"rstrip": true,
|
||||
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|
||||
},
|
||||
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|
||||
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||||
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|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
501273
tokenizer.json
Normal file
501273
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
791
tokenizer_config.json
Normal file
791
tokenizer_config.json
Normal file
@@ -0,0 +1,791 @@
|
||||
{
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100256": {
|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"100257": {
|
||||
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|
||||
"lstrip": true,
|
||||
"normalized": false,
|
||||
"rstrip": true,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100258": {
|
||||
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|
||||
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|
||||
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|
||||
"rstrip": true,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100259": {
|
||||
"content": "<|fim_middle|>",
|
||||
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|
||||
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|
||||
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|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100260": {
|
||||
"content": "<|fim_suffix|>",
|
||||
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|
||||
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|
||||
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|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100261": {
|
||||
"content": "<|dummy_1|>",
|
||||
"lstrip": true,
|
||||
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|
||||
"rstrip": true,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100262": {
|
||||
"content": "<|dummy_2|>",
|
||||
"lstrip": true,
|
||||
"normalized": false,
|
||||
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|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100263": {
|
||||
"content": "<|dummy_3|>",
|
||||
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|
||||
"normalized": false,
|
||||
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|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100264": {
|
||||
"content": "<|im_start|>",
|
||||
"lstrip": true,
|
||||
"normalized": false,
|
||||
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|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100265": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": true,
|
||||
"normalized": false,
|
||||
"rstrip": true,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100266": {
|
||||
"content": "<|im_sep|>",
|
||||
"lstrip": true,
|
||||
"normalized": false,
|
||||
"rstrip": true,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100267": {
|
||||
"content": "<|dummy_4|>",
|
||||
"lstrip": true,
|
||||
"normalized": false,
|
||||
"rstrip": true,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100268": {
|
||||
"content": "<|dummy_5|>",
|
||||
"lstrip": true,
|
||||
"normalized": false,
|
||||
"rstrip": true,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100269": {
|
||||
"content": "<|dummy_6|>",
|
||||
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|
||||
"normalized": false,
|
||||
"rstrip": true,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100270": {
|
||||
"content": "<|dummy_7|>",
|
||||
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|
||||
"normalized": false,
|
||||
"rstrip": true,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100271": {
|
||||
"content": "<|dummy_8|>",
|
||||
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|
||||
"normalized": false,
|
||||
"rstrip": true,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100272": {
|
||||
"content": "<|dummy_9|>",
|
||||
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|
||||
"normalized": false,
|
||||
"rstrip": true,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100273": {
|
||||
"content": "<|dummy_10|>",
|
||||
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|
||||
"normalized": false,
|
||||
"rstrip": true,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100274": {
|
||||
"content": "<|dummy_11|>",
|
||||
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|
||||
"normalized": false,
|
||||
"rstrip": true,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100275": {
|
||||
"content": "<|dummy_12|>",
|
||||
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|
||||
"normalized": false,
|
||||
"rstrip": true,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100276": {
|
||||
"content": "<|endofprompt|>",
|
||||
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|
||||
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|
||||
"rstrip": true,
|
||||
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|
||||
"special": true
|
||||
},
|
||||
"100277": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"special": true
|
||||
},
|
||||
"100278": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"special": true
|
||||
},
|
||||
"100279": {
|
||||
"content": "<|dummy_15|>",
|
||||
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|
||||
"normalized": false,
|
||||
"rstrip": true,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"100280": {
|
||||
"content": "<|dummy_16|>",
|
||||
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|
||||
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|
||||
"rstrip": true,
|
||||
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|
||||
"special": true
|
||||
},
|
||||
"100281": {
|
||||
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|
||||
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|
||||
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|
||||
"rstrip": true,
|
||||
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|
||||
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|
||||
},
|
||||
"100282": {
|
||||
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|
||||
"lstrip": true,
|
||||
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|
||||
"rstrip": true,
|
||||
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|
||||
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|
||||
},
|
||||
"100283": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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|
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|
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|
||||
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|
||||
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|
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|
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|
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|
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|
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|
||||
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|
||||
"chat_template": "{% for message in messages %}{% if (message['role'] == 'system') %}{{'<|im_start|>system<|im_sep|>' + message['content'] + '<|im_end|>'}}{% elif (message['role'] == 'user') %}{{'<|im_start|>user<|im_sep|>' + message['content'] + '<|im_end|>'}}{% elif (message['role'] == 'assistant') %}{{'<|im_start|>assistant<|im_sep|>' + message['content'] + '<|im_end|>'}}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant<|im_sep|>' }}{% endif %}"
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user