Update README.md

README.md

@@ -41,8 +41,8 @@ GGML versions are not yet provided, as there is not yet support for SuperHOT in
 
 ## Repositories available
 
-* [4-bit GPTQ models for GPU inference](https://huggingface.co/TheBloke/Vicuna-13B-1.3.0-SuperHOT-8K-GPTQ)
-* [Unquantised SuperHOT fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/TheBloke/Vicuna-13B-1.3.0-SuperHOT-8K-fp16)
+* [4-bit GPTQ models for GPU inference](https://huggingface.co/TheBloke/Vicuna-13B-1-3-SuperHOT-8K-GPTQ)
+* [Unquantised SuperHOT fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/TheBloke/Vicuna-13B-1-3-SuperHOT-8K-fp16)
 * [Unquantised base fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/lmsys/vicuna-13b-v1.3)
 
 ## How to easily download and use this model in text-generation-webui with ExLlama
@@ -50,12 +50,12 @@ GGML versions are not yet provided, as there is not yet support for SuperHOT in
 Please make sure you're using the latest version of text-generation-webui
 
 1. Click the **Model tab**.
-2. Under **Download custom model or LoRA**, enter `TheBloke/Vicuna-13B-1.3.0-SuperHOT-8K-GPTQ`.
+2. Under **Download custom model or LoRA**, enter `TheBloke/Vicuna-13B-1-3-SuperHOT-8K-GPTQ`.
 3. Click **Download**.
 4. The model will start downloading. Once it's finished it will say "Done"
 5. Untick **Autoload the model**
 6. In the top left, click the refresh icon next to **Model**.
-7. In the **Model** dropdown, choose the model you just downloaded: `Vicuna-13B-1.3.0-SuperHOT-8K-GPTQ`
+7. In the **Model** dropdown, choose the model you just downloaded: `Vicuna-13B-1-3-SuperHOT-8K-GPTQ`
 8. To use the increased context, set the **Loader** to **ExLlama**, set **max_seq_len** to 8192 or 4096, and set **compress_pos_emb** to **4** for 8192 context, or to **2** for 4096 context.
 9. Now click **Save Settings** followed by **Reload**
 10. The model will automatically load, and is now ready for use!
@@ -78,7 +78,7 @@ from transformers import AutoTokenizer, pipeline, logging
 from auto_gptq import AutoGPTQForCausalLM, BaseQuantizeConfig
 import argparse
 
-model_name_or_path = "TheBloke/Vicuna-13B-1.3.0-SuperHOT-8K-GPTQ"
+model_name_or_path = "TheBloke/Vicuna-13B-1-3-SuperHOT-8K-GPTQ"
 model_basename = "vicuna-13b-1.3.0-superhot-8k-GPTQ-4bit-128g.no-act.order"
 
 use_triton = False