Mention rwkv v6 in the readmes. (#1784)

README.md

@@ -79,7 +79,7 @@ We also provide a some command line based examples using state of the art models
 - [StarCoder](./candle-examples/examples/bigcode/) and
   [StarCoder2](./candle-examples/examples/starcoder2/): LLM specialized to code generation.
 - [Qwen1.5](./candle-examples/examples/qwen/): Bilingual (English/Chinese) LLMs.
-- [RWKV v5](./candle-examples/examples/rwkv/): An RNN with transformer level LLM
+- [RWKV v5 and v6](./candle-examples/examples/rwkv/): An RNN with transformer level LLM
   performance.
 - [Replit-code-v1.5](./candle-examples/examples/replit-code/): a 3.3b LLM specialized for code completion.
 - [Yi-6B / Yi-34B](./candle-examples/examples/yi/): two bilingual
@@ -203,7 +203,7 @@ If you have an addition to this list, please submit a pull request.
         - Bert.
         - Yi-6B and Yi-34B.
         - Qwen1.5.
-        - RWKV.
+        - RWKV v5 and v6.
     - Quantized LLMs.
         - Llama 7b, 13b, 70b, as well as the chat and code variants.
         - Mistral 7b, and 7b instruct.

candle-examples/examples/rwkv/README.md

@@ -2,8 +2,8 @@
 
 The [RWKV model](https://wiki.rwkv.com/) is a recurrent neural network model
 with performance on par with transformer architectures. Several variants are
-available, candle implements the v5 version and can be used with Eagle 7B([blog
-post](https://blog.rwkv.com/p/eagle-7b-soaring-past-transformers)).
+available, candle implements the v5 and v6 versions and can be used with
+Eagle 7B([blog post](https://blog.rwkv.com/p/eagle-7b-soaring-past-transformers)).
 
 ```bash
 $ cargo run --example rwkv --release -- --prompt "The smallest prime is "