Merge dev branch

README.md

@@ -11,7 +11,7 @@ Its goal is to become the [AUTOMATIC1111/stable-diffusion-webui](https://github.
 ## Features
 
 * 3 interface modes: default (two columns), notebook, and chat.
-* Multiple model backends: [Transformers](https://github.com/huggingface/transformers), [llama.cpp](https://github.com/ggerganov/llama.cpp) (through [llama-cpp-python](https://github.com/abetlen/llama-cpp-python)), [ExLlamaV2](https://github.com/turboderp/exllamav2), [AutoGPTQ](https://github.com/PanQiWei/AutoGPTQ), [AutoAWQ](https://github.com/casper-hansen/AutoAWQ), [GPTQ-for-LLaMa](https://github.com/qwopqwop200/GPTQ-for-LLaMa), [CTransformers](https://github.com/marella/ctransformers), [QuIP#](https://github.com/Cornell-RelaxML/quip-sharp).
+* Multiple model backends: [Transformers](https://github.com/huggingface/transformers), [llama.cpp](https://github.com/ggerganov/llama.cpp) (through [llama-cpp-python](https://github.com/abetlen/llama-cpp-python)), [ExLlamaV2](https://github.com/turboderp/exllamav2), [AutoGPTQ](https://github.com/PanQiWei/AutoGPTQ), [AutoAWQ](https://github.com/casper-hansen/AutoAWQ), [GPTQ-for-LLaMa](https://github.com/qwopqwop200/GPTQ-for-LLaMa), [QuIP#](https://github.com/Cornell-RelaxML/quip-sharp).
 * Dropdown menu for quickly switching between different models.
 * Large number of extensions (built-in and user-contributed), including Coqui TTS for realistic voice outputs, Whisper STT for voice inputs, translation, [multimodal pipelines](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/multimodal), vector databases, Stable Diffusion integration, and a lot more. See [the wiki](https://github.com/oobabooga/text-generation-webui/wiki/07-%E2%80%90-Extensions) and [the extensions directory](https://github.com/oobabooga/text-generation-webui-extensions) for details.
 * [Chat with custom characters](https://github.com/oobabooga/text-generation-webui/wiki/03-%E2%80%90-Parameters-Tab#character).
@@ -221,7 +221,7 @@ List of command-line flags
 
 | Flag                                       | Description |
 |--------------------------------------------|-------------|
-| `--loader LOADER`                          | Choose the model loader manually, otherwise, it will get autodetected. Valid options: Transformers, llama.cpp, llamacpp_HF, ExLlamav2_HF, ExLlamav2, AutoGPTQ, AutoAWQ, GPTQ-for-LLaMa, ctransformers, QuIP#. |
+| `--loader LOADER`                          | Choose the model loader manually, otherwise, it will get autodetected. Valid options: Transformers, llama.cpp, llamacpp_HF, ExLlamav2_HF, ExLlamav2, AutoGPTQ, AutoAWQ, GPTQ-for-LLaMa, QuIP#. |
 
 #### Accelerate/transformers
 
@@ -308,12 +308,6 @@ List of command-line flags
 | `--checkpoint CHECKPOINT` | The path to the quantized checkpoint file. If not specified, it will be automatically detected. |
 | `--monkey-patch`          | Apply the monkey patch for using LoRAs with quantized models. |
 
-#### ctransformers
-
-| Flag        | Description |
-|-------------|-------------|
-| `--model_type MODEL_TYPE` | Model type of pre-quantized model. Currently gpt2, gptj, gptneox, falcon, llama, mpt, starcoder (gptbigcode), dollyv2, and replit are supported. |
-
 #### HQQ
 
 | Flag        | Description |

docs/04 - Model Tab.md

@@ -105,12 +105,6 @@ It has an additional parameter:
 
 * **logits_all**: Needs to be checked if you want to evaluate the perplexity of the llama.cpp model using the "Training" > "Perplexity evaluation" tab. Otherwise, leave it unchecked, as it makes prompt processing slower.
 
-### ctransformers
-
-Loads: GGUF/GGML models.
-
-Similar to llama.cpp but it works for certain GGUF/GGML models not originally supported by llama.cpp like Falcon, StarCoder, StarChat, and GPT-J.
-
 ### AutoAWQ
 
 Loads: AWQ models.

docs/08 - Additional Tips.md

@@ -13,29 +13,6 @@ Source: https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/1126
 
 This file will be automatically detected the next time you start the web UI.
 
-## GPT-4chan
-
-[GPT-4chan](https://huggingface.co/ykilcher/gpt-4chan) has been shut down from Hugging Face, so you need to download it elsewhere. You have two options:
-
-* Torrent: [16-bit](https://archive.org/details/gpt4chan_model_float16) / [32-bit](https://archive.org/details/gpt4chan_model)
-* Direct download: [16-bit](https://theswissbay.ch/pdf/_notpdf_/gpt4chan_model_float16/) / [32-bit](https://theswissbay.ch/pdf/_notpdf_/gpt4chan_model/)
-
-The 32-bit version is only relevant if you intend to run the model in CPU mode. Otherwise, you should use the 16-bit version.
-
-After downloading the model, follow these steps:
-
-1. Place the files under `models/gpt4chan_model_float16` or `models/gpt4chan_model`.
-2. Place GPT-J 6B's config.json file in that same folder: [config.json](https://huggingface.co/EleutherAI/gpt-j-6B/raw/main/config.json).
-3. Download GPT-J 6B's tokenizer files (they will be automatically detected when you attempt to load GPT-4chan):
-
-```
-python download-model.py EleutherAI/gpt-j-6B --text-only
-```
-
-When you load this model in default or notebook modes, the "HTML" tab will show the generated text in 4chan format:
-
-![Image3](https://github.com/oobabooga/screenshots/raw/main/gpt4chan.png)
-
 ## Using LoRAs with GPTQ-for-LLaMa
 
 This requires using a monkey patch that is supported by this web UI: https://github.com/johnsmith0031/alpaca_lora_4bit

docs/What Works.md

@@ -10,7 +10,6 @@
 | AutoGPTQ       |       ✅       |           ❌            |       ❌       |          ✅          |           ✅          |
 | AutoAWQ        |       ?        |           ❌            |       ?        |          ?           |           ✅          |
 | GPTQ-for-LLaMa |       ✅\*\*   |           ✅\*\*\*      |       ✅       |          ✅          |           ✅          |
-| ctransformers  |       ❌       |           ❌            |       ❌       |          ❌          |           ❌          |
 | QuIP#          |       ?        |           ?             |       ?        |          ?           |           ✅          |
 | HQQ            |       ?        |           ?             |       ?        |          ?           |           ✅          |
 

modules/html_generator.py

@@ -16,8 +16,6 @@
 
 with open(Path(__file__).resolve().parent / '../css/html_readable_style.css', 'r') as f:
     readable_css = f.read()
-with open(Path(__file__).resolve().parent / '../css/html_4chan_style.css', 'r') as css_f:
-    _4chan_css = css_f.read()
 with open(Path(__file__).resolve().parent / '../css/html_instruct_style.css', 'r') as f:
     instruct_css = f.read()
 
@@ -118,63 +116,6 @@ def generate_basic_html(string):
     return string
 
 
-def process_post(post, c):
-    t = post.split('\n')
-    number = t[0].split(' ')[1]
-    if len(t) > 1:
-        src = '\n'.join(t[1:])
-    else:
-        src = ''
-    src = re.sub('>', '>', src)
-    src = re.sub('(&gt;&gt;[0-9]*)', '<span class="quote">\\1</span>', src)
-    src = re.sub('\n', '<br>\n', src)
-    src = f'<blockquote class="message_4chan">{src}\n'
-    src = f'<span class="name">Anonymous </span> <span class="number">No.{number}</span>\n{src}'
-    return src
-
-
-def generate_4chan_html(f):
-    posts = []
-    post = ''
-    c = -2
-    for line in f.splitlines():
-        line += "\n"
-        if line == '-----\n':
-            continue
-        elif line.startswith('--- '):
-            c += 1
-            if post != '':
-                src = process_post(post, c)
-                posts.append(src)
-            post = line
-        else:
-            post += line
-
-    if post != '':
-        src = process_post(post, c)
-        posts.append(src)
-
-    for i in range(len(posts)):
-        if i == 0:
-            posts[i] = f'<div class="op">{posts[i]}</div>\n'
-        else:
-            posts[i] = f'<div class="reply">{posts[i]}</div>\n'
-
-    output = ''
-    output += f'<style>{_4chan_css}</style><div id="parent"><div id="container">'
-    for post in posts:
-        output += post
-
-    output += '</div></div>'
-    output = output.split('\n')
-    for i in range(len(output)):
-        output[i] = re.sub(r'^(&gt;(.*?)(<br>|</div>))', r'<span class="greentext">\1</span>', output[i])
-        output[i] = re.sub(r'^<blockquote class="message_4chan">(&gt;(.*?)(<br>|</div>))', r'<blockquote class="message_4chan"><span class="greentext">\1</span>', output[i])
-
-    output = '\n'.join(output)
-    return output
-
-
 def make_thumbnail(image):
     image = image.resize((350, round(image.size[1] / image.size[0] * 350)), Image.Resampling.LANCZOS)
     if image.size[1] > 470:

modules/loaders.py

@@ -138,15 +138,6 @@
         'no_use_fast',
         'gptq_for_llama_info',
     ],
-    'ctransformers': [
-        'n_ctx',
-        'n_gpu_layers',
-        'n_batch',
-        'threads',
-        'model_type',
-        'no_mmap',
-        'mlock'
-    ],
     'QuIP#': [
         'trust_remote_code',
         'no_use_fast',
@@ -332,13 +323,6 @@ def transformers_samplers():
         'skip_special_tokens',
         'auto_max_new_tokens',
     },
-    'ctransformers': {
-        'temperature',
-        'top_p',
-        'top_k',
-        'repetition_penalty',
-        'repetition_penalty_range',
-    },
 }
 
 loaders_model_types = {
@@ -348,19 +332,6 @@ def transformers_samplers():
         "opt",
         "gptj"
     ],
-    'ctransformers': [
-        "None",
-        "gpt2",
-        "gptj",
-        "gptneox",
-        "llama",
-        "mpt",
-        "dollyv2",
-        "replit",
-        "starcoder",
-        "gptbigcode",
-        "falcon"
-    ],
 }