Instructions to use albertkingdom/deepseek-coder-7b-text2sql-magicoder-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use albertkingdom/deepseek-coder-7b-text2sql-magicoder-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-7b-instruct-v1.5") model = PeftModel.from_pretrained(base_model, "albertkingdom/deepseek-coder-7b-text2sql-magicoder-lora") - Notebooks
- Google Colab
- Kaggle
Commit ·
f15478b
1
Parent(s): bfc87ac
Add LoRA adapter
Browse files- README.md +62 -0
- adapter_config.json +43 -0
- adapter_model.safetensors +3 -0
- chat_template.jinja +26 -0
- special_tokens_map.json +17 -0
- tokenizer.json +0 -0
- tokenizer_config.json +146 -0
- training_args.bin +3 -0
README.md
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---
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base_model: deepseek-ai/deepseek-coder-7b-instruct-v1.5
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library_name: peft
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model_name: sql-adapter
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tags:
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- base_model:adapter:deepseek-ai/deepseek-coder-7b-instruct-v1.5
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- lora
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- sft
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- transformers
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- trl
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licence: license
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pipeline_tag: text-generation
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---
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# Model Card for sql-adapter
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This model is a fine-tuned version of [deepseek-ai/deepseek-coder-7b-instruct-v1.5](https://huggingface.co/deepseek-ai/deepseek-coder-7b-instruct-v1.5).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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```python
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from transformers import pipeline
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question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
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generator = pipeline("text-generation", model="None", device="cuda")
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output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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print(output["generated_text"])
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```
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## Training procedure
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This model was trained with SFT.
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### Framework versions
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- PEFT 0.18.0
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- TRL: 0.26.2
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- Transformers: 4.57.3
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- Pytorch: 2.9.1+cu128
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- Datasets: 4.4.2
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- Tokenizers: 0.22.1
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## Citations
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Cite TRL as:
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```bibtex
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@misc{vonwerra2022trl,
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title = {{TRL: Transformer Reinforcement Learning}},
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author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
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year = 2020,
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journal = {GitHub repository},
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publisher = {GitHub},
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howpublished = {\url{https://github.com/huggingface/trl}}
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}
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```
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adapter_config.json
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{
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"alora_invocation_tokens": null,
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"alpha_pattern": {},
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"arrow_config": null,
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"auto_mapping": null,
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"base_model_name_or_path": "deepseek-ai/deepseek-coder-7b-instruct-v1.5",
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"bias": "none",
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"corda_config": null,
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"ensure_weight_tying": false,
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"eva_config": null,
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"exclude_modules": null,
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 32,
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"lora_bias": false,
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"lora_dropout": 0.05,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"peft_version": "0.18.0",
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"qalora_group_size": 16,
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"r": 16,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"q_proj",
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"k_proj",
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"v_proj",
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"o_proj"
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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"trainable_token_indices": null,
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"use_dora": false,
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"use_qalora": false,
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"use_rslora": false
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}
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:6dc0af55be3a57e2c06c8711404b08f4275720b9c14cf5c0d3d17404efb6d30b
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size 31489712
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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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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": "<|EOT|>"
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}
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tokenizer.json
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The diff for this file is too large to render.
See raw diff
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tokenizer_config.json
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{
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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 |
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"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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"100000": {
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| 7 |
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"content": "<|begin▁of▁sentence|>",
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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": true
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| 13 |
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},
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| 14 |
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"100001": {
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| 15 |
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"content": "<|end▁of▁sentence|>",
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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 |
+
"single_word": false,
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| 20 |
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"special": true
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| 21 |
+
},
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| 22 |
+
"100002": {
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| 23 |
+
"content": "ø",
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| 24 |
+
"lstrip": false,
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| 25 |
+
"normalized": true,
|
| 26 |
+
"rstrip": false,
|
| 27 |
+
"single_word": false,
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| 28 |
+
"special": false
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| 29 |
+
},
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| 30 |
+
"100003": {
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| 31 |
+
"content": "ö",
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| 32 |
+
"lstrip": false,
|
| 33 |
+
"normalized": true,
|
| 34 |
+
"rstrip": false,
|
| 35 |
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"single_word": false,
|
| 36 |
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"special": false
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| 37 |
+
},
|
| 38 |
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"100004": {
|
| 39 |
+
"content": "ú",
|
| 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
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| 45 |
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},
|
| 46 |
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"100005": {
|
| 47 |
+
"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,
|
| 52 |
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"special": false
|
| 53 |
+
},
|
| 54 |
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"100006": {
|
| 55 |
+
"content": "õ",
|
| 56 |
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"lstrip": false,
|
| 57 |
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"normalized": true,
|
| 58 |
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"rstrip": false,
|
| 59 |
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"single_word": false,
|
| 60 |
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"special": false
|
| 61 |
+
},
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| 62 |
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"100007": {
|
| 63 |
+
"content": "÷",
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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,
|
| 67 |
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"single_word": false,
|
| 68 |
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"special": false
|
| 69 |
+
},
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| 70 |
+
"100008": {
|
| 71 |
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"content": "û",
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| 72 |
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"lstrip": false,
|
| 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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},
|
| 78 |
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"100009": {
|
| 79 |
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"content": "ý",
|
| 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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},
|
| 86 |
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"100010": {
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| 87 |
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"content": "À",
|
| 88 |
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"lstrip": false,
|
| 89 |
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"normalized": true,
|
| 90 |
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"rstrip": false,
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| 91 |
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"single_word": false,
|
| 92 |
+
"special": false
|
| 93 |
+
},
|
| 94 |
+
"100011": {
|
| 95 |
+
"content": "ù",
|
| 96 |
+
"lstrip": false,
|
| 97 |
+
"normalized": true,
|
| 98 |
+
"rstrip": false,
|
| 99 |
+
"single_word": false,
|
| 100 |
+
"special": false
|
| 101 |
+
},
|
| 102 |
+
"100012": {
|
| 103 |
+
"content": "Á",
|
| 104 |
+
"lstrip": false,
|
| 105 |
+
"normalized": true,
|
| 106 |
+
"rstrip": false,
|
| 107 |
+
"single_word": false,
|
| 108 |
+
"special": false
|
| 109 |
+
},
|
| 110 |
+
"100013": {
|
| 111 |
+
"content": "þ",
|
| 112 |
+
"lstrip": false,
|
| 113 |
+
"normalized": true,
|
| 114 |
+
"rstrip": false,
|
| 115 |
+
"single_word": false,
|
| 116 |
+
"special": false
|
| 117 |
+
},
|
| 118 |
+
"100014": {
|
| 119 |
+
"content": "ü",
|
| 120 |
+
"lstrip": false,
|
| 121 |
+
"normalized": true,
|
| 122 |
+
"rstrip": false,
|
| 123 |
+
"single_word": false,
|
| 124 |
+
"special": false
|
| 125 |
+
},
|
| 126 |
+
"100015": {
|
| 127 |
+
"content": "<|EOT|>",
|
| 128 |
+
"lstrip": false,
|
| 129 |
+
"normalized": true,
|
| 130 |
+
"rstrip": false,
|
| 131 |
+
"single_word": false,
|
| 132 |
+
"special": true
|
| 133 |
+
}
|
| 134 |
+
},
|
| 135 |
+
"bos_token": "<|begin▁of▁sentence|>",
|
| 136 |
+
"clean_up_tokenization_spaces": false,
|
| 137 |
+
"eos_token": "<|EOT|>",
|
| 138 |
+
"extra_special_tokens": {},
|
| 139 |
+
"legacy": true,
|
| 140 |
+
"model_max_length": 4096,
|
| 141 |
+
"pad_token": "<|EOT|>",
|
| 142 |
+
"sp_model_kwargs": {},
|
| 143 |
+
"tokenizer_class": "LlamaTokenizerFast",
|
| 144 |
+
"unk_token": null,
|
| 145 |
+
"use_default_system_prompt": false
|
| 146 |
+
}
|
training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:25941047b55392a17105f7d307e5e32a8ca111a740a6b127f23e5d258067463c
|
| 3 |
+
size 6225
|