BUAADreamer
/

Yi-VL-34B-hf

@@ -2,199 +2,59 @@
 library_name: transformers
 tags:
 - llama-factory
 ---
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 library_name: transformers
 tags:
 - llama-factory
+- yi-vl
+- llava
+license: other
+language:
+- zh
+- en
+pipeline_tag: visual-question-answering
 ---
+This is the Huggingface version of [Yi-VL-34B](https://huggingface.co/01-ai/Yi-VL-34B) model.
+You may use this model for fine-tuning in downstream tasks, we recommend using our efficient fine-tuning toolkit. https://github.com/hiyouga/LLaMA-Factory
+- **Developed by:** [01-AI](https://www.01.ai/).
+- **Language(s) (NLP):** Chinese/English
+- **License:** [Yi Series Model License](https://huggingface.co/01-ai/Yi-VL-34B/blob/main/LICENSE)
+Usage:
+```python
+import requests
+from PIL import Image
+import torch
+from transformers import AutoProcessor, AutoModelForVision2Seq
+model_id = "BUAADreamer/Yi-VL-34B-hf"
+messages = [
+  { "role": "user", "content": "What's in the picture?" }
+]
+model = AutoModelForVision2Seq.from_pretrained(
+    model_id,
+    torch_dtype=torch.float16,
+    low_cpu_mem_usage=True,
+).to(0)
+processor = AutoProcessor.from_pretrained(model_id)
+text = [processor.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=False)]
+images = [Image.open(requests.get(image_file, stream=True).raw)]
+inputs = processor(text=prompt, images=images, return_tensors='pt').to(0, torch.float16)
+output = model.generate(**inputs, max_new_tokens=200)
+output = processor.batch_decode(output, skip_special_tokens=True)
+print(output.split("Assistant:")[-1].strip())
+```
+You could also alternatively launch a Web demo by using the CLI command in [LLaMA-Factory](https://github.com/hiyouga/LLaMA-Factory)
+```bash
+llamafactory-cli webchat \
+--model_name_or_path BUAADreamer/Yi-VL-34B-hf \
+--template yi_vl \
+--visual_inputs
+```