Training in progress, step 110
Browse files- README.md +4 -4
- adapter_config.json +6 -6
- adapter_model.safetensors +1 -1
README.md
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---
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base_model: unsloth/Qwen2.5-3B
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library_name: transformers
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model_name: LinalgZero-SFT-LoRA
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tags:
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- generated_from_trainer
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- trl
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licence: license
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---
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# Model Card for LinalgZero-SFT-LoRA
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This model is a fine-tuned version of [unsloth/Qwen2.5-3B](https://huggingface.co/unsloth/Qwen2.5-3B).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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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="atomwalk12/LinalgZero-SFT-LoRA
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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/walks/huggingface/runs/
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This model was trained with SFT.
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---
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base_model: unsloth/Qwen2.5-3B
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library_name: transformers
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+
model_name: LinalgZero-SFT-LoRA
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tags:
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- generated_from_trainer
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- trl
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licence: license
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---
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+
# Model Card for LinalgZero-SFT-LoRA
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This model is a fine-tuned version of [unsloth/Qwen2.5-3B](https://huggingface.co/unsloth/Qwen2.5-3B).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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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="atomwalk12/LinalgZero-SFT-LoRA", 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/walks/huggingface/runs/uiedinmd)
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This model was trained with SFT.
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adapter_config.json
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": [
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"
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"
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],
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"peft_type": "LORA",
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"peft_version": "0.18.0",
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"
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"
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"k_proj",
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"o_proj",
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"down_proj",
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"
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"
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": [
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"lm_head",
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"embed_tokens"
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],
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"peft_type": "LORA",
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"peft_version": "0.18.0",
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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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"up_proj",
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"k_proj",
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"o_proj",
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"down_proj",
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"gate_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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adapter_model.safetensors
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