Update to MiniCPM-V 2.6

docs/faqs.md

@@ -0,0 +1,30 @@
+### FAQs
+
+<details>
+<summary>Q:  How to choose between sampling or beam search for inference </summary>
+
+In various scenarios, the quality of results obtained from beam search and sampling decoding strategies can vary. You can determine your decoding strategy based on the following aspects:
+
+If you have the following needs, consider using sampling decoding:
+
+1. You require faster inference speed.
+2. You wish for a streaming generation approach.
+3. Your task necessitates some open-ended responses.
+
+If your task is about providing deterministic answers, you might want to experiment with beam search to see if it can achieve better outcomes.
+</details>
+
+
+<details>
+<summary>Q: How to ensure that the model generates results of sufficient length</summary>
+
+We've observed that during multi-language inference on MiniCPM-V 2.6, the generation sometimes ends prematurely. You can improve the results by passing a `min_new_tokens` parameter.
+```python
+res = model.chat(
+    image=None,
+    msgs=msgs,
+    tokenizer=tokenizer,
+    min_new_tokens=100
+)
+```
+</details>