Upload README.md

README.md

@@ -80,15 +80,8 @@ A chat between a curious user and an artificial intelligence assistant. The assi
 ```
 
 <!-- prompt-template end -->
-<!-- licensing start -->
-## Licensing
 
-The creator of the source model has listed its license as `other`, and this quantization has therefore used that same license.
 
-As this model is based on Llama 2, it is also subject to the Meta Llama 2 license terms, and the license files for that are additionally included. It should therefore be considered as being claimed to be licensed under both licenses. I contacted Hugging Face for clarification on dual licensing but they do not yet have an official position. Should this change, or should Meta provide any feedback on this situation, I will update this section accordingly.
-
-In the meantime, any questions regarding licensing, and in particular how these two licenses might interact, should be directed to the original model repository: [Eric Hartford's WizardLM-13b-V1.0-Uncensored](https://huggingface.co/ehartford/WizardLM-13b-V1.0-Uncensored).
-<!-- licensing end -->
 <!-- compatibility_gguf start -->
 ## Compatibility
 
@@ -147,7 +140,7 @@ 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/WizardLM-13B-V1.0-Uncensored-GGUF and below it, a specific filename to download, such as: wizardlm-13b-v1.0-uncensored.q4_K_M.gguf.
+Under Download Model, you can enter the model repo: TheBloke/WizardLM-13B-V1.0-Uncensored-GGUF and below it, a specific filename to download, such as: wizardlm-13b-v1.0-uncensored.Q4_K_M.gguf.
 
 Then click Download.
 
@@ -162,7 +155,7 @@ pip3 install huggingface-hub>=0.17.1
 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/WizardLM-13B-V1.0-Uncensored-GGUF wizardlm-13b-v1.0-uncensored.q4_K_M.gguf --local-dir . --local-dir-use-symlinks False
+huggingface-cli download TheBloke/WizardLM-13B-V1.0-Uncensored-GGUF wizardlm-13b-v1.0-uncensored.Q4_K_M.gguf --local-dir . --local-dir-use-symlinks False
 ```
 
 <details>
@@ -185,7 +178,7 @@ 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/WizardLM-13B-V1.0-Uncensored-GGUF wizardlm-13b-v1.0-uncensored.q4_K_M.gguf --local-dir . --local-dir-use-symlinks False
+HUGGINGFACE_HUB_ENABLE_HF_TRANSFER=1 huggingface-cli download TheBloke/WizardLM-13B-V1.0-Uncensored-GGUF wizardlm-13b-v1.0-uncensored.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.
@@ -198,7 +191,7 @@ 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 wizardlm-13b-v1.0-uncensored.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 wizardlm-13b-v1.0-uncensored.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.
@@ -238,7 +231,7 @@ 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/WizardLM-13B-V1.0-Uncensored-GGUF", model_file="wizardlm-13b-v1.0-uncensored.q4_K_M.gguf", model_type="llama", gpu_layers=50)
+llm = AutoModelForCausalLM.from_pretrained("TheBloke/WizardLM-13B-V1.0-Uncensored-GGUF", model_file="wizardlm-13b-v1.0-uncensored.Q4_K_M.gguf", model_type="llama", gpu_layers=50)
 
 print(llm("AI is going to"))
 ```
@@ -289,24 +282,6 @@ And thank you again to a16z for their generous grant.
 <!-- original-model-card start -->
 # Original model card: Eric Hartford's WizardLM-13b-V1.0-Uncensored
 
-
-This is a retraining of https://huggingface.co/WizardLM/WizardLM-13B-V1.0 with a filtered dataset, intended to reduce refusals, avoidance, and bias.
-
-Note that LLaMA itself has inherent ethical beliefs, so there's no such thing as a "truly uncensored" model.  But this model will be more compliant than WizardLM/WizardLM-7B-V1.0.
-
-Shout out to the open source AI/ML community, and everyone who helped me out.
-
-Note: An uncensored model has no guardrails. You are responsible for anything you do with the model, just as you are responsible for anything you do with any dangerous object such as a knife, gun, lighter, or car. Publishing anything this model generates is the same as publishing it yourself. You are responsible for the content you publish, and you cannot blame the model any more than you can blame the knife, gun, lighter, or car for what you do with it.
-
-Like WizardLM/WizardLM-13B-V1.0, this model is trained with Vicuna-1.1 style prompts.
-
-```
-You are a helpful AI assistant.
-
-USER: <prompt>
-ASSISTANT:
-```
-
-Thank you [chirper.ai](https://chirper.ai) for sponsoring some of my compute!
+No original model card was available.
 
 <!-- original-model-card end -->