thanks to TheBloke ❤

README.md

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+---
+license: apache-2.0
+datasets:
+- ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered
+inference: false
+---
+
+# WizardLM - uncensored: An Instruction-following LLM Using Evol-Instruct
+
+These files are GPTQ 4bit model files for [Eric Hartford's 'uncensored' version of WizardLM](https://huggingface.co/ehartford/WizardLM-7B-Uncensored).
+
+It is the result of quantising to 4bit using [GPTQ-for-LLaMa](https://github.com/qwopqwop200/GPTQ-for-LLaMa).
+
+Eric did a fresh 7B training using the WizardLM method, on [a dataset edited to remove all the "I'm sorry.." type ChatGPT responses](https://huggingface.co/datasets/ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered).
+
+## Other repositories available
+
+* [4bit GPTQ models for GPU inference](https://huggingface.co/TheBloke/WizardLM-7B-uncensored-GPTQ)
+* [4bit and 5bit GGML models for CPU inference](https://huggingface.co/TheBloke/WizardLM-7B-uncensored-GGML)
+* [Eric's unquantised model in HF format](https://huggingface.co/ehartford/WizardLM-7B-Uncensored)
+
+## How to easily download and use this model in text-generation-webui
+
+Open the text-generation-webui UI as normal.
+
+1. Click the **Model tab**.
+2. Under **Download custom model or LoRA**, enter `TheBloke/WizardLM-7B-uncensored-GPTQ`.
+3. Click **Download**.
+4. Wait until it says it's finished downloading.
+5. Click the **Refresh** icon next to **Model** in the top left.
+6. In the **Model drop-down**: choose the model you just downloaded, `WizardLM-7B-uncensored-GPTQ`.
+7. If you see an error in the bottom right, ignore it - it's temporary.
+8. Fill out the `GPTQ parameters` on the right: `Bits = 4`, `Groupsize = 128`, `model_type = Llama`
+9. Click **Save settings for this model** in the top right.
+10. Click **Reload the Model** in the top right.
+11. Once it says it's loaded, click the **Text Generation tab** and enter a prompt!
+
+## Provided files
+
+**Compatible file - WizardLM-7B-uncensored-GPTQ-4bit-128g.compat.no-act-order.safetensors**
+
+In the `main` branch - the default one - you will find `WizardLM-7B-uncensored-GPTQ-4bit-128g.compat.no-act-order.safetensors`
+
+This will work with all versions of GPTQ-for-LLaMa. It has maximum compatibility
+
+It was created without the `--act-order` parameter. It may have slightly lower inference quality compared to the other file, but is guaranteed to work on all versions of GPTQ-for-LLaMa and text-generation-webui.
+
+* `wizard-vicuna-13B-GPTQ-4bit.compat.no-act-order.safetensors`
+  * Works with all versions of GPTQ-for-LLaMa code, both Triton and CUDA branches
+  * Works with text-generation-webui one-click-installers
+  * Parameters: Groupsize = 128g. No act-order.
+  * Command used to create the GPTQ:
+    ```
+    python llama.py models/ehartford_WizardLM-7B-Uncensored c4 --wbits 4 --true-sequential --groupsize 128 --save_safetensors /workspace/eric-gptq/WizardLM-7B-uncensored-GPTQ-4bit-128g.compat.no-act-order.safetensors
+    ```
+   
+# Eric's original model card
+
+This is WizardLM trained with a subset of the dataset - responses that contained alignment / moralizing were removed.  The intent is to train a WizardLM that doesn't have alignment built-in, so that alignment (of any sort) can be added separately with for example with a RLHF LoRA.
+
+Shout out to the open source AI/ML community, and everyone who helped me out, including Rohan, TheBloke, and Caseus
+
+# WizardLM's original model card
+
+Overview of Evol-Instruct
+Evol-Instruct is a novel method using LLMs instead of humans to automatically mass-produce open-domain instructions of various difficulty levels and skills range, to improve the performance of LLMs.
+
+![info](https://github.com/nlpxucan/WizardLM/raw/main/imgs/git_overall.png)
+![info](https://github.com/nlpxucan/WizardLM/raw/main/imgs/git_running.png)

WizardLM-7B-uncensored-GPTQ-4bit-128g.compat.no-act-order.safetensors

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added_tokens.json

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+{
+  "[PAD]": 32000
+}

config.json

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+{
+  "_name_or_path": "/workspace/llama-7b-hf",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 11008,
+  "max_position_embeddings": 2048,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "pad_token_id": 0,
+  "rms_norm_eps": 1e-06,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.29.0.dev0",
+  "use_cache": true,
+  "vocab_size": 32001
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "pad_token_id": 0,
+  "transformers_version": "4.29.0.dev0"
+}

special_tokens_map.json

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+{
+  "bos_token": "</s>",
+  "eos_token": "</s>",
+  "pad_token": "[PAD]",
+  "unk_token": "</s>"
+}

tokenizer.model

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+size 499723

tokenizer_config.json

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+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "bos_token": {
+    "__type": "AddedToken",
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "clean_up_tokenization_spaces": false,
+  "eos_token": {
+    "__type": "AddedToken",
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "model_max_length": 2048,
+  "pad_token": null,
+  "padding_side": "right",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": {
+    "__type": "AddedToken",
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  }
+}