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Update app.py
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app.py
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@@ -10,8 +10,10 @@ from text_generation import Client
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from share_btn import community_icon_html, loading_icon_html, share_js, share_btn_css
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HF_TOKEN = os.environ.get("HF_TOKEN", None)
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API_URL = "https://api-inference.huggingface.co/models/bigcode/starcoder"
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API_URL_BASE ="https://api-inference.huggingface.co/models/bigcode/starcoderbase"
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FIM_PREFIX = "<fim_prefix>"
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FIM_MIDDLE = "<fim_middle>"
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@@ -20,30 +22,39 @@ FIM_SUFFIX = "<fim_suffix>"
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FIM_INDICATOR = "<FILL_HERE>"
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FORMATS = """## Model Formats
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The model is pretrained on code and is formatted with special tokens in addition to the pure code data,\
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such as prefixes specifying the source of the file or tokens separating code from a commit message.\
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Use these templates to explore the model's capacities:
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### 1. Prefixes 🏷️
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For pure code files, use any combination of the following prefixes:
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```
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<reponame>REPONAME<filename>FILENAME<gh_stars>STARS\ncode<|endoftext|>
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```
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STARS can be one of: 0, 1-10, 10-100, 100-1000, 1000+
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### 2. Commits 💾
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The commits data is formatted as follows:
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```
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<commit_before>code<commit_msg>text<commit_after>code<|endoftext|>
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```
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### 3. Jupyter Notebooks 📓
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The model is trained on Jupyter notebooks as Python scripts and structured formats like:
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```
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<start_jupyter><jupyter_text>text<jupyter_code>code<jupyter_output>output<jupyter_text>
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```
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### 4. Issues 🐛
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We also trained on GitHub issues using the following formatting:
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```
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<issue_start><issue_comment>text<issue_comment>...<issue_closed>
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```
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### 5. Fill-in-the-middle 🧩
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Fill in the middle requires rearranging the model inputs. The playground handles this for you - all you need is to specify where to fill:
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```
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@@ -71,6 +82,9 @@ client = Client(
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client_base = Client(
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API_URL_BASE, headers={"Authorization": f"Bearer {HF_TOKEN}"},
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)
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def generate(
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prompt, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0, version="StarCoder",
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@@ -101,6 +115,8 @@ def generate(
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if version == "StarCoder":
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stream = client.generate_stream(prompt, **generate_kwargs)
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else:
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stream = client_base.generate_stream(prompt, **generate_kwargs)
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@@ -126,6 +142,7 @@ def generate(
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examples = [
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"X_train, y_train, X_test, y_test = train_test_split(X, y, test_size=0.1)\n\n# Train a logistic regression model, predict the labels on the test set and compute the accuracy score",
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"// Returns every other value in the array as a new array.\nfunction everyOther(arr) {",
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"def alternating(list1, list2):\n results = []\n for i in range(min(len(list1), len(list2))):\n results.append(list1[i])\n results.append(list2[i])\n if len(list1) > len(list2):\n <FILL_HERE>\n else:\n results.extend(list2[i+1:])\n return results",
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]
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description = """
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<div style="text-align: center;">
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<h1>
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-
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-
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</div>
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"""
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disclaimer = """⚠️<b>Any use or sharing of this demo constitues your acceptance of the BigCode [OpenRAIL-M](https://huggingface.co/spaces/bigcode/bigcode-model-license-agreement) License Agreement and the use restrictions included within.</b>\
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@@ -161,15 +185,23 @@ disclaimer = """⚠️<b>Any use or sharing of this demo constitues your accepta
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with gr.Blocks(theme=theme, analytics_enabled=False, css=css) as demo:
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with gr.Column():
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gr.Markdown(description)
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with gr.Row():
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with gr.Column():
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instruction = gr.Textbox(
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placeholder="Enter your code here",
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-
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elem_id="q-input",
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)
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submit = gr.Button("Generate", variant="primary")
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output = gr.Code(elem_id="q-output", lines=30)
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with gr.Row():
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with gr.Column():
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with gr.Accordion("Advanced settings", open=False):
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@@ -213,13 +245,7 @@ with gr.Blocks(theme=theme, analytics_enabled=False, css=css) as demo:
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interactive=True,
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info="Penalize repeated tokens",
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)
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-
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version = gr.Dropdown(
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["StarCoderBase", "StarCoder"],
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value="StarCoder",
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label="Version",
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info="",
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)
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gr.Markdown(disclaimer)
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with gr.Group(elem_id="share-btn-container"):
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community_icon = gr.HTML(community_icon_html, visible=True)
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from share_btn import community_icon_html, loading_icon_html, share_js, share_btn_css
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HF_TOKEN = os.environ.get("HF_TOKEN", None)
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API_URL = "https://api-inference.huggingface.co/models/bigcode/starcoder"
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API_URL_BASE ="https://api-inference.huggingface.co/models/bigcode/starcoderbase"
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API_URL_PLUS = "https://api-inference.huggingface.co/models/bigcode/starcoderplus"
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FIM_PREFIX = "<fim_prefix>"
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FIM_MIDDLE = "<fim_middle>"
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FIM_INDICATOR = "<FILL_HERE>"
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FORMATS = """## Model Formats
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+
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The model is pretrained on code and is formatted with special tokens in addition to the pure code data,\
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such as prefixes specifying the source of the file or tokens separating code from a commit message.\
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Use these templates to explore the model's capacities:
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+
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### 1. Prefixes 🏷️
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For pure code files, use any combination of the following prefixes:
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+
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```
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<reponame>REPONAME<filename>FILENAME<gh_stars>STARS\ncode<|endoftext|>
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```
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STARS can be one of: 0, 1-10, 10-100, 100-1000, 1000+
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+
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### 2. Commits 💾
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The commits data is formatted as follows:
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```
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<commit_before>code<commit_msg>text<commit_after>code<|endoftext|>
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```
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### 3. Jupyter Notebooks 📓
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The model is trained on Jupyter notebooks as Python scripts and structured formats like:
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```
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<start_jupyter><jupyter_text>text<jupyter_code>code<jupyter_output>output<jupyter_text>
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```
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+
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### 4. Issues 🐛
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We also trained on GitHub issues using the following formatting:
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```
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<issue_start><issue_comment>text<issue_comment>...<issue_closed>
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```
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### 5. Fill-in-the-middle 🧩
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Fill in the middle requires rearranging the model inputs. The playground handles this for you - all you need is to specify where to fill:
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```
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client_base = Client(
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API_URL_BASE, headers={"Authorization": f"Bearer {HF_TOKEN}"},
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)
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client_plus = Client(
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API_URL_PLUS, headers={"Authorization": f"Bearer {HF_TOKEN}"},
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)
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def generate(
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prompt, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0, version="StarCoder",
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if version == "StarCoder":
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stream = client.generate_stream(prompt, **generate_kwargs)
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elif version == "StarCoderPlus":
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stream = client_plus.generate_stream(prompt, **generate_kwargs)
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else:
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stream = client_base.generate_stream(prompt, **generate_kwargs)
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examples = [
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"X_train, y_train, X_test, y_test = train_test_split(X, y, test_size=0.1)\n\n# Train a logistic regression model, predict the labels on the test set and compute the accuracy score",
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"// Returns every other value in the array as a new array.\nfunction everyOther(arr) {",
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"Poor English: She no went to the market. Corrected English:",
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"def alternating(list1, list2):\n results = []\n for i in range(min(len(list1), len(list2))):\n results.append(list1[i])\n results.append(list2[i])\n if len(list1) > len(list2):\n <FILL_HERE>\n else:\n results.extend(list2[i+1:])\n return results",
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]
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description = """
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<div style="text-align: center;">
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<h1> ⭐ StarCoder <span style='color: #e6b800;'>Models</span> Playground</h1>
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</div>
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<div style="text-align: left;">
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<p>This is a demo to generate text and code with the following StarCoder models:</p>
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<ul>
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<li><a href="https://huggingface.co/bigcode/starcoderplus" style='color: #e6b800;'>StarCoderPlus</a>: A finetuned version of StarCoderBase on English web data, making it strong in both English text and code generation.</li>
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<li><a href="https://huggingface.co/bigcode/starcoderbase" style='color: #e6b800;'>StarCoderBase</a>: A code generation model trained on 80+ programming languages, providing broad language coverage for code generation tasks.</li>
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<li><a href="https://huggingface.co/bigcode/starcoder" style='color: #e6b800;'>StarCoder</a>: A finetuned version of StarCoderBase specifically focused on Python, while also maintaining strong performance on other programming languages.</li>
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</ul>
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<p><b>Please note:</b> These models are not designed for instruction purposes. If you're looking for instruction or want to chat with a fine-tuned model, you can visit the <a href="https://huggingface.co/spaces/HuggingFaceH4/starchat-playground">StarChat Playground</a>.</p>
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</div>
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"""
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disclaimer = """⚠️<b>Any use or sharing of this demo constitues your acceptance of the BigCode [OpenRAIL-M](https://huggingface.co/spaces/bigcode/bigcode-model-license-agreement) License Agreement and the use restrictions included within.</b>\
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with gr.Blocks(theme=theme, analytics_enabled=False, css=css) as demo:
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with gr.Column():
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gr.Markdown(description)
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with gr.Row():
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version = gr.Dropdown(
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["StarCoderPlus", "StarCoderBase", "StarCoder"],
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value="StarCoderPlus",
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label="Model",
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info="Choose a model from the list",
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)
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with gr.Row():
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with gr.Column():
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instruction = gr.Textbox(
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placeholder="Enter your code here",
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lines=5,
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label="Input",
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elem_id="q-input",
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)
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submit = gr.Button("Generate", variant="primary")
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output = gr.Code(elem_id="q-output", lines=30, label="Output")
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with gr.Row():
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with gr.Column():
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with gr.Accordion("Advanced settings", open=False):
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interactive=True,
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info="Penalize repeated tokens",
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)
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gr.Markdown(disclaimer)
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with gr.Group(elem_id="share-btn-container"):
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community_icon = gr.HTML(community_icon_html, visible=True)
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