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  1. README.md +4 -4
  2. adapter_model.safetensors +1 -1
README.md CHANGED
@@ -1,7 +1,7 @@
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  ---
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  base_model: Qwen/Qwen2-VL-7B-Instruct
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  library_name: transformers
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- model_name: Qwen2-VL-7B-Instruct-finetune-2024-12-05_10-51-27
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  tags:
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  - generated_from_trainer
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  - trl
@@ -9,7 +9,7 @@ tags:
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  licence: license
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  ---
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- # Model Card for Qwen2-VL-7B-Instruct-finetune-2024-12-05_10-51-27
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  This model is a fine-tuned version of [Qwen/Qwen2-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct).
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  It has been trained using [TRL](https://github.com/huggingface/trl).
@@ -20,14 +20,14 @@ 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="UCSC-Admire/Qwen2-VL-7B-Instruct-finetune-2024-12-05_10-51-27", 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/sam-silver/qwen2-7b-instruct-trl-sft/runs/zpmitfn1)
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  This model was trained with SFT.
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  ---
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  base_model: Qwen/Qwen2-VL-7B-Instruct
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  library_name: transformers
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+ model_name: Qwen2-VL-7B-Instruct-finetune-2024-12-05_11-26-00
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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 Qwen2-VL-7B-Instruct-finetune-2024-12-05_11-26-00
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  This model is a fine-tuned version of [Qwen/Qwen2-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct).
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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="UCSC-Admire/Qwen2-VL-7B-Instruct-finetune-2024-12-05_11-26-00", 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/sam-silver/qwen2-7b-instruct-trl-sft/runs/3fudqvfl)
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  This model was trained with SFT.
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adapter_model.safetensors CHANGED
@@ -1,3 +1,3 @@
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