Instructions to use NabeelMirza/Mathstral_model_4bit_Training_5_epoch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NabeelMirza/Mathstral_model_4bit_Training_5_epoch with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("NabeelMirza/Mathstral_model_4bit_Training_5_epoch", dtype="auto") - Notebooks
- Google Colab
- Kaggle
NabeelMirza/Trained_Model/Mathtral_4bit_Training_5_Epochs
Browse files- README.md +57 -0
- adapter_config.json +35 -0
- adapter_model.safetensors +3 -0
- runs/Nov13_11-04-57_015f1904151b/events.out.tfevents.1731495931.015f1904151b.609.0 +3 -0
- runs/Nov13_11-33-27_5b2fd95c0657/events.out.tfevents.1731497632.5b2fd95c0657.891.0 +3 -0
- runs/Nov13_11-35-28_5b2fd95c0657/events.out.tfevents.1731497741.5b2fd95c0657.891.1 +3 -0
- special_tokens_map.json +24 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +0 -0
- training_args.bin +3 -0
README.md
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---
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base_model: mistralai/Mathstral-7B-v0.1
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library_name: transformers
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model_name: Mathstral_model_4bit_Training_5_epoch
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tags:
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- generated_from_trainer
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- trl
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- sft
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licence: license
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---
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# Model Card for Mathstral_model_4bit_Training_5_epoch
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This model is a fine-tuned version of [mistralai/Mathstral-7B-v0.1](https://huggingface.co/mistralai/Mathstral-7B-v0.1).
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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="NabeelMirza/Mathstral_model_4bit_Training_5_epoch", 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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/nmirza2013-kanbina/huggingface/runs/jbgqlo0c)
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This model was trained with SFT.
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### Framework versions
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- TRL: 0.12.0
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- Transformers: 4.46.2
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- Pytorch: 2.4.1+cu121
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- Datasets: 3.1.0
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- Tokenizers: 0.20.3
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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 Gallouédec},
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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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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "mistralai/Mathstral-7B-v0.1",
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"bias": "none",
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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_dropout": 0.1,
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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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"r": 64,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"down_proj",
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"q_proj",
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"gate_proj",
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"v_proj",
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"lm_head",
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"up_proj",
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"o_proj",
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"k_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": 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 sha256:1777d14d29fe3077d2083da73b39100a6e3de9abec456070a601adb477b91843
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size 1217458040
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runs/Nov13_11-04-57_015f1904151b/events.out.tfevents.1731495931.015f1904151b.609.0
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version https://git-lfs.github.com/spec/v1
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runs/Nov13_11-33-27_5b2fd95c0657/events.out.tfevents.1731497632.5b2fd95c0657.891.0
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version https://git-lfs.github.com/spec/v1
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runs/Nov13_11-35-28_5b2fd95c0657/events.out.tfevents.1731497741.5b2fd95c0657.891.1
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version https://git-lfs.github.com/spec/v1
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size 69988
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": "</s>",
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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer.json
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tokenizer.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:59f95e28944c062244741268596badc900df86c7f5ded05088d2da22a7379e06
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size 587583
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tokenizer_config.json
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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size 5688
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