Upload README.md

README.md

@@ -150,7 +150,7 @@ The following clients/libraries will automatically download models for you, prov
 
 ### In `text-generation-webui`
 
-Under Download Model, you can enter the model repo: TheBloke/hippogriff-30b-chat-GGUF and below it, a specific filename to download, such as: hippogriff-30b.q4_K_M.gguf.
+Under Download Model, you can enter the model repo: TheBloke/hippogriff-30b-chat-GGUF and below it, a specific filename to download, such as: hippogriff-30b.Q4_K_M.gguf.
 
 Then click Download.
 
@@ -159,13 +159,13 @@ Then click Download.
 I recommend using the `huggingface-hub` Python library:
 
 ```shell
-pip3 install huggingface-hub>=0.17.1
+pip3 install huggingface-hub
 ```
 
 Then you can download any individual model file to the current directory, at high speed, with a command like this:
 
 ```shell
-huggingface-cli download TheBloke/hippogriff-30b-chat-GGUF hippogriff-30b.q4_K_M.gguf --local-dir . --local-dir-use-symlinks False
+huggingface-cli download TheBloke/hippogriff-30b-chat-GGUF hippogriff-30b.Q4_K_M.gguf --local-dir . --local-dir-use-symlinks False
 ```
 
 <details>
@@ -188,10 +188,10 @@ pip3 install hf_transfer
 And set environment variable `HF_HUB_ENABLE_HF_TRANSFER` to `1`:
 
 ```shell
-HUGGINGFACE_HUB_ENABLE_HF_TRANSFER=1 huggingface-cli download TheBloke/hippogriff-30b-chat-GGUF hippogriff-30b.q4_K_M.gguf --local-dir . --local-dir-use-symlinks False
+HUGGINGFACE_HUB_ENABLE_HF_TRANSFER=1 huggingface-cli download TheBloke/hippogriff-30b-chat-GGUF hippogriff-30b.Q4_K_M.gguf --local-dir . --local-dir-use-symlinks False
 ```
 
-Windows CLI users: Use `set HUGGINGFACE_HUB_ENABLE_HF_TRANSFER=1` before running the download command.
+Windows Command Line users: You can set the environment variable by running `set HUGGINGFACE_HUB_ENABLE_HF_TRANSFER=1` before the download command.
 </details>
 <!-- README_GGUF.md-how-to-download end -->
 
@@ -201,7 +201,7 @@ Windows CLI users: Use `set HUGGINGFACE_HUB_ENABLE_HF_TRANSFER=1` before running
 Make sure you are using `llama.cpp` from commit [d0cee0d36d5be95a0d9088b674dbb27354107221](https://github.com/ggerganov/llama.cpp/commit/d0cee0d36d5be95a0d9088b674dbb27354107221) or later.
 
 ```shell
-./main -ngl 32 -m hippogriff-30b.q4_K_M.gguf --color -c 4096 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: {prompt} ASSISTANT:"
+./main -ngl 32 -m hippogriff-30b.Q4_K_M.gguf --color -c 4096 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: {prompt} ASSISTANT:"
 ```
 
 Change `-ngl 32` to the number of layers to offload to GPU. Remove it if you don't have GPU acceleration.
@@ -241,7 +241,7 @@ CT_METAL=1 pip install ctransformers>=0.2.24 --no-binary ctransformers
 from ctransformers import AutoModelForCausalLM
 
 # Set gpu_layers to the number of layers to offload to GPU. Set to 0 if no GPU acceleration is available on your system.
-llm = AutoModelForCausalLM.from_pretrained("TheBloke/hippogriff-30b-chat-GGUF", model_file="hippogriff-30b.q4_K_M.gguf", model_type="llama", gpu_layers=50)
+llm = AutoModelForCausalLM.from_pretrained("TheBloke/hippogriff-30b-chat-GGUF", model_file="hippogriff-30b.Q4_K_M.gguf", model_type="llama", gpu_layers=50)
 
 print(llm("AI is going to"))
 ```