Instructions to use rohhaiil/SysMLv2-Repair-DeepSeek-Coder-6.7B-Instruct-Code-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rohhaiil/SysMLv2-Repair-DeepSeek-Coder-6.7B-Instruct-Code-LoRA with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-6.7b-instruct") model = PeftModel.from_pretrained(base_model, "rohhaiil/SysMLv2-Repair-DeepSeek-Coder-6.7B-Instruct-Code-LoRA") - Transformers
How to use rohhaiil/SysMLv2-Repair-DeepSeek-Coder-6.7B-Instruct-Code-LoRA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="rohhaiil/SysMLv2-Repair-DeepSeek-Coder-6.7B-Instruct-Code-LoRA") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rohhaiil/SysMLv2-Repair-DeepSeek-Coder-6.7B-Instruct-Code-LoRA", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use rohhaiil/SysMLv2-Repair-DeepSeek-Coder-6.7B-Instruct-Code-LoRA with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "rohhaiil/SysMLv2-Repair-DeepSeek-Coder-6.7B-Instruct-Code-LoRA" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rohhaiil/SysMLv2-Repair-DeepSeek-Coder-6.7B-Instruct-Code-LoRA", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/rohhaiil/SysMLv2-Repair-DeepSeek-Coder-6.7B-Instruct-Code-LoRA
- SGLang
How to use rohhaiil/SysMLv2-Repair-DeepSeek-Coder-6.7B-Instruct-Code-LoRA 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 "rohhaiil/SysMLv2-Repair-DeepSeek-Coder-6.7B-Instruct-Code-LoRA" \ --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": "rohhaiil/SysMLv2-Repair-DeepSeek-Coder-6.7B-Instruct-Code-LoRA", "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 "rohhaiil/SysMLv2-Repair-DeepSeek-Coder-6.7B-Instruct-Code-LoRA" \ --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": "rohhaiil/SysMLv2-Repair-DeepSeek-Coder-6.7B-Instruct-Code-LoRA", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use rohhaiil/SysMLv2-Repair-DeepSeek-Coder-6.7B-Instruct-Code-LoRA with Docker Model Runner:
docker model run hf.co/rohhaiil/SysMLv2-Repair-DeepSeek-Coder-6.7B-Instruct-Code-LoRA
Upload 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 +23 -0
- tokenizer.json +0 -0
- tokenizer_config.json +194 -0
- training_args.bin +3 -0
README.md
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| 1 |
+
---
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+
base_model: deepseek-ai/deepseek-coder-6.7b-instruct
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library_name: peft
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model_name: code
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tags:
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- base_model:adapter:deepseek-ai/deepseek-coder-6.7b-instruct
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- lora
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+
- sft
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| 9 |
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- transformers
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| 10 |
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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 code
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This model is a fine-tuned version of [deepseek-ai/deepseek-coder-6.7b-instruct](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-instruct).
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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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| 41 |
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- TRL: 0.26.2
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- Transformers: 4.57.3
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| 43 |
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- Pytorch: 2.2.2
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- Datasets: 4.4.2
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- Tokenizers: 0.22.2
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## Citations
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Cite TRL as:
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```bibtex
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| 54 |
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@misc{vonwerra2022trl,
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| 55 |
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title = {{TRL: Transformer Reinforcement Learning}},
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| 56 |
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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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| 57 |
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year = 2020,
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| 58 |
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journal = {GitHub repository},
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| 59 |
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publisher = {GitHub},
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| 60 |
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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-6.7b-instruct",
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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": 16,
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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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| 27 |
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"qalora_group_size": 16,
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"r": 8,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"v_proj",
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"o_proj",
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"k_proj",
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"q_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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| 41 |
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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 sha256:730c24d8dabd45ce95cd4e0d36f08c9738b4c8b146ecb9cf3d9e126973e2df1a
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size 33588528
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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": {
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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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| 21 |
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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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The diff for this file is too large to render.
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tokenizer_config.json
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{
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| 2 |
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"add_bos_token": true,
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| 3 |
+
"add_eos_token": false,
|
| 4 |
+
"add_prefix_space": null,
|
| 5 |
+
"added_tokens_decoder": {
|
| 6 |
+
"32000": {
|
| 7 |
+
"content": "õ",
|
| 8 |
+
"lstrip": false,
|
| 9 |
+
"normalized": true,
|
| 10 |
+
"rstrip": false,
|
| 11 |
+
"single_word": false,
|
| 12 |
+
"special": false
|
| 13 |
+
},
|
| 14 |
+
"32001": {
|
| 15 |
+
"content": "÷",
|
| 16 |
+
"lstrip": false,
|
| 17 |
+
"normalized": true,
|
| 18 |
+
"rstrip": false,
|
| 19 |
+
"single_word": false,
|
| 20 |
+
"special": false
|
| 21 |
+
},
|
| 22 |
+
"32002": {
|
| 23 |
+
"content": "Á",
|
| 24 |
+
"lstrip": false,
|
| 25 |
+
"normalized": true,
|
| 26 |
+
"rstrip": false,
|
| 27 |
+
"single_word": false,
|
| 28 |
+
"special": false
|
| 29 |
+
},
|
| 30 |
+
"32003": {
|
| 31 |
+
"content": "ý",
|
| 32 |
+
"lstrip": false,
|
| 33 |
+
"normalized": true,
|
| 34 |
+
"rstrip": false,
|
| 35 |
+
"single_word": false,
|
| 36 |
+
"special": false
|
| 37 |
+
},
|
| 38 |
+
"32004": {
|
| 39 |
+
"content": "À",
|
| 40 |
+
"lstrip": false,
|
| 41 |
+
"normalized": true,
|
| 42 |
+
"rstrip": false,
|
| 43 |
+
"single_word": false,
|
| 44 |
+
"special": false
|
| 45 |
+
},
|
| 46 |
+
"32005": {
|
| 47 |
+
"content": "ÿ",
|
| 48 |
+
"lstrip": false,
|
| 49 |
+
"normalized": true,
|
| 50 |
+
"rstrip": false,
|
| 51 |
+
"single_word": false,
|
| 52 |
+
"special": false
|
| 53 |
+
},
|
| 54 |
+
"32006": {
|
| 55 |
+
"content": "ø",
|
| 56 |
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"lstrip": false,
|
| 57 |
+
"normalized": true,
|
| 58 |
+
"rstrip": false,
|
| 59 |
+
"single_word": false,
|
| 60 |
+
"special": false
|
| 61 |
+
},
|
| 62 |
+
"32007": {
|
| 63 |
+
"content": "ú",
|
| 64 |
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"lstrip": false,
|
| 65 |
+
"normalized": true,
|
| 66 |
+
"rstrip": false,
|
| 67 |
+
"single_word": false,
|
| 68 |
+
"special": false
|
| 69 |
+
},
|
| 70 |
+
"32008": {
|
| 71 |
+
"content": "þ",
|
| 72 |
+
"lstrip": false,
|
| 73 |
+
"normalized": true,
|
| 74 |
+
"rstrip": false,
|
| 75 |
+
"single_word": false,
|
| 76 |
+
"special": false
|
| 77 |
+
},
|
| 78 |
+
"32009": {
|
| 79 |
+
"content": "ü",
|
| 80 |
+
"lstrip": false,
|
| 81 |
+
"normalized": true,
|
| 82 |
+
"rstrip": false,
|
| 83 |
+
"single_word": false,
|
| 84 |
+
"special": false
|
| 85 |
+
},
|
| 86 |
+
"32010": {
|
| 87 |
+
"content": "ù",
|
| 88 |
+
"lstrip": false,
|
| 89 |
+
"normalized": true,
|
| 90 |
+
"rstrip": false,
|
| 91 |
+
"single_word": false,
|
| 92 |
+
"special": false
|
| 93 |
+
},
|
| 94 |
+
"32011": {
|
| 95 |
+
"content": "ö",
|
| 96 |
+
"lstrip": false,
|
| 97 |
+
"normalized": true,
|
| 98 |
+
"rstrip": false,
|
| 99 |
+
"single_word": false,
|
| 100 |
+
"special": false
|
| 101 |
+
},
|
| 102 |
+
"32012": {
|
| 103 |
+
"content": "û",
|
| 104 |
+
"lstrip": false,
|
| 105 |
+
"normalized": true,
|
| 106 |
+
"rstrip": false,
|
| 107 |
+
"single_word": false,
|
| 108 |
+
"special": false
|
| 109 |
+
},
|
| 110 |
+
"32013": {
|
| 111 |
+
"content": "<|begin▁of▁sentence|>",
|
| 112 |
+
"lstrip": false,
|
| 113 |
+
"normalized": true,
|
| 114 |
+
"rstrip": false,
|
| 115 |
+
"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 |
+
"sp_model_kwargs": {},
|
| 191 |
+
"tokenizer_class": "LlamaTokenizerFast",
|
| 192 |
+
"unk_token": null,
|
| 193 |
+
"use_default_system_prompt": false
|
| 194 |
+
}
|
training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b39efeaaef854facdbc2ee4a48d8c865f00bec3b33cb6e33adb0268ec8096b58
|
| 3 |
+
size 5880
|