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            <h1 id="seo-header">【记录】win10平台6G显存运行Qwen-1.8B</h1>
            
              <p id="updated-time" class="note note-info" style="">
                
                  
                    Last updated on March 29, 2024 am
                  
                
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              <div class="markdown-body">
                
                <p><a href="https://hexo.limour.top/go/#aHR0cHM6Ly9naXRodWIuY29tL2dnZXJnYW5vdi9sbGFtYS5jcHA=" rel="noopener external nofollow noreferrer">Llama.cpp</a> 能 CPU &amp; GPU 环境混合推理，这里记录一下在 windows10 平台上运行 <a href="https://hexo.limour.top/go/#aHR0cHM6Ly9odWdnaW5nZmFjZS5jby9Rd2VuL1F3ZW4tMV84Qg==" rel="noopener external nofollow noreferrer">Qwen-1.8B</a> 的过程，显卡是 1660Ti 。</p>
<h2 id="准备模型">准备模型</h2>
<ul>
<li><a href="/-ji-lu--an-zhuang-conda-bing-geng-huan-qing-hua-yuan">安装conda</a></li>
<li><a href="/Use-Tunnel-to-speed-up-the-connection-of-VPS">Tun模式</a>(管理员权限)</li>
</ul>
<figure class="highlight powershell"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br></pre></td><td class="code"><pre><code class="hljs powershell">conda create <span class="hljs-literal">-n</span> llamaConvert python=<span class="hljs-number">3.10</span> git <span class="hljs-literal">-c</span> conda<span class="hljs-literal">-forge</span><br>conda activate llamaConvert<br><span class="hljs-built_in">cd</span> D:\llama<br>git clone <span class="hljs-literal">--depth</span>=<span class="hljs-number">1</span> https://github.com/ggerganov/llama.cpp.git<br><span class="hljs-built_in">cd</span> llama.cpp<br>python <span class="hljs-literal">-m</span> pip install <span class="hljs-literal">-r</span> requirements.txt<br>pip install tiktoken<br></code></pre></td></tr></table></figure>
<figure class="highlight powershell"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br></pre></td><td class="code"><pre><code class="hljs powershell">python <span class="hljs-literal">-c</span> <span class="hljs-string">&quot;from huggingface_hub import snapshot_download; snapshot_download(repo_id=&#x27;Qwen/Qwen-1_8B-Chat&#x27;, local_dir=r&#x27;D:\qwen&#x27;, ignore_patterns=[&#x27;*.h5&#x27;, &#x27;*.ot&#x27;, &#x27;*.msgpack&#x27;, &#x27;*.safetensors&#x27;])&quot;</span><br><span class="hljs-built_in">cd</span> D:\qwen<br>D:\aria2\aria2c.exe <span class="hljs-literal">--all-proxy</span>=<span class="hljs-string">&#x27;http://127.0.0.1:7890&#x27;</span> <span class="hljs-literal">-o</span> <span class="hljs-string">&#x27;model-00001-of-00002.safetensors&#x27;</span> <span class="hljs-string">&quot;https://huggingface.co/Qwen/Qwen-1_8B-Chat/resolve/main/model-00001-of-00002.safetensors?download=true&quot;</span><br>D:\aria2\aria2c.exe <span class="hljs-literal">--all-proxy</span>=<span class="hljs-string">&#x27;http://127.0.0.1:7890&#x27;</span> <span class="hljs-literal">-o</span> <span class="hljs-string">&#x27;model-00002-of-00002.safetensors&#x27;</span> <span class="hljs-string">&quot;https://huggingface.co/Qwen/Qwen-1_8B-Chat/resolve/main/model-00002-of-00002.safetensors?download=true&quot;</span><br></code></pre></td></tr></table></figure>
<figure class="highlight powershell"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br></pre></td><td class="code"><pre><code class="hljs powershell"><span class="hljs-built_in">cd</span> D:\llama\llama.cpp<br>python <span class="hljs-built_in">convert-hf</span><span class="hljs-literal">-to-gguf</span>.py D:\qwen<br><span class="hljs-comment"># Model successfully exported to &#x27;D:\qwen\ggml-model-f16.gguf&#x27;</span><br></code></pre></td></tr></table></figure>
<h2 id="运行模型">运行模型</h2>
<ul>
<li>下载 <a href="https://hexo.limour.top/go/#aHR0cHM6Ly9naXRodWIuY29tL2dnZXJnYW5vdi9sbGFtYS5jcHAvcmVsZWFzZXM=" rel="noopener external nofollow noreferrer">llama-b1732-bin-win-cublas-cu12.2.0-x64.zip</a></li>
<li>提取文件到 <code>D:\llama</code></li>
</ul>
<figure class="highlight powershell"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br></pre></td><td class="code"><pre><code class="hljs powershell">conda create <span class="hljs-literal">-n</span> llamaCpp libcublas cuda<span class="hljs-literal">-toolkit</span> git <span class="hljs-literal">-c</span> nvidia <span class="hljs-literal">-c</span> conda<span class="hljs-literal">-forge</span><br>conda activate llamaCpp<br><span class="hljs-built_in">cd</span> D:\llama ; .\main.exe <span class="hljs-comment">## 检查能否正确运行</span><br><span class="hljs-built_in">cd</span> D:\llama ; .\quantize.exe <span class="hljs-literal">--help</span> <span class="hljs-comment">## 自己决定量化方式</span><br>.\quantize.exe D:\qwen\ggml<span class="hljs-literal">-model-f16</span>.gguf .\qwen<span class="hljs-literal">-1_8-f16</span>.gguf <span class="hljs-built_in">COPY</span><br>.\server.exe <span class="hljs-literal">-m</span> .\qwen<span class="hljs-literal">-1_8-f16</span>.gguf <span class="hljs-literal">-c</span> <span class="hljs-number">4096</span> <span class="hljs-literal">--n-gpu-layers</span> <span class="hljs-number">50</span> <span class="hljs-comment">## 调节 n-gpu-layers 平衡 CPU &amp; GPU</span><br></code></pre></td></tr></table></figure>
<ul>
<li>访问 <code>http://127.0.0.1:8080</code> 选择 <code>Completion</code> 进行测试</li>
</ul>
<h2 id="微调模型">微调模型</h2>
<ul>
<li><a href="https://hexo.limour.top/go/#aHR0cHM6Ly9odWdnaW5nZmFjZS5jby9kYXRhc2V0cy9hNjg2ZDM4MC9oLWNvcnB1cy0yMDIz" rel="noopener external nofollow noreferrer">h-corpus数据集</a></li>
<li><a href="https://hexo.limour.top/go/#aHR0cHM6Ly9naXRodWIuY29tL1F3ZW5MTS9Rd2VuL2Jsb2IvbWFpbi9SRUFETUVfQ04ubWQjJUU1JUJFJUFFJUU4JUIwJTgz" rel="noopener external nofollow noreferrer">官方微调教程</a></li>
</ul>
<h2 id="附加-Yi-6B-Chat">附加 Yi-6B-Chat</h2>
<p><a href="https://hexo.limour.top/go/#aHR0cHM6Ly9odWdnaW5nZmFjZS5jby8wMS1haS9ZaS02Qi1DaGF0" rel="noopener external nofollow noreferrer">Yi-6B</a>是零一万物开源的双语语言模型，经过3T多语种语料库的训练，在语言理解、常识推理、阅读理解等方面有一定潜力。</p>
<figure class="highlight powershell"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br></pre></td><td class="code"><pre><code class="hljs powershell"><span class="hljs-built_in">cd</span> D:\models\<span class="hljs-number">01</span>yi<br>D:\aria2\aria2c.exe <span class="hljs-literal">--all-proxy</span>=<span class="hljs-string">&#x27;http://127.0.0.1:7890&#x27;</span> <span class="hljs-literal">-o</span> <span class="hljs-string">&#x27;model-00001-of-00003.safetensors&#x27;</span> <span class="hljs-string">&quot;https://huggingface.co/01-ai/Yi-6B-Chat/resolve/main/model-00001-of-00003.safetensors?download=true&quot;</span><br>D:\aria2\aria2c.exe <span class="hljs-literal">--all-proxy</span>=<span class="hljs-string">&#x27;http://127.0.0.1:7890&#x27;</span> <span class="hljs-literal">-o</span> <span class="hljs-string">&#x27;model-00002-of-00003.safetensors&#x27;</span> <span class="hljs-string">&quot;https://huggingface.co/01-ai/Yi-6B-Chat/resolve/main/model-00002-of-00003.safetensors?download=true&quot;</span><br>D:\aria2\aria2c.exe <span class="hljs-literal">--all-proxy</span>=<span class="hljs-string">&#x27;http://127.0.0.1:7890&#x27;</span> <span class="hljs-literal">-o</span> <span class="hljs-string">&#x27;model-00003-of-00003.safetensors&#x27;</span>  https://huggingface.co/<span class="hljs-number">01</span><span class="hljs-literal">-ai</span>/Yi<span class="hljs-literal">-6B-Chat</span>/resolve/main/model<span class="hljs-literal">-00003-of-00003</span>.safetensors?download=true<br>conda activate llamaConvert<br>python <span class="hljs-literal">-c</span> <span class="hljs-string">&quot;from huggingface_hub import snapshot_download; snapshot_download(repo_id=&#x27;01-ai/Yi-6B-Chat&#x27;, local_dir=r&#x27;D:\models\01yi&#x27;, ignore_patterns=[&#x27;*.h5&#x27;, &#x27;*.ot&#x27;, &#x27;*.msgpack&#x27;, &#x27;*.safetensors&#x27;])&quot;</span><br></code></pre></td></tr></table></figure>
<figure class="highlight powershell"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br></pre></td><td class="code"><pre><code class="hljs powershell">conda activate llamaConvert<br><span class="hljs-built_in">cd</span> D:\llama\llama.cpp<br>python convert.py D:\models\<span class="hljs-number">01</span>yi<br><span class="hljs-comment"># Wrote D:\models\01yi\ggml-model-f16.gguf</span><br>conda activate llamaCpp<br><span class="hljs-built_in">cd</span> D:\llama ; .\quantize.exe <span class="hljs-literal">--help</span><br>.\quantize.exe D:\models\<span class="hljs-number">01</span>yi\ggml<span class="hljs-literal">-model-f16</span>.gguf .\<span class="hljs-number">01</span>yi<span class="hljs-literal">-6b-Q4_K_M</span>.gguf Q4_K_M<br>.\server.exe <span class="hljs-literal">-m</span> .\<span class="hljs-number">01</span>yi<span class="hljs-literal">-6b-Q4_K_M</span>.gguf <span class="hljs-literal">-c</span> <span class="hljs-number">4096</span> <span class="hljs-literal">--n-gpu-layers</span> <span class="hljs-number">50</span><br></code></pre></td></tr></table></figure>
<h2 id="附加-百川2">附加 百川2</h2>
<figure class="highlight powershell"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br></pre></td><td class="code"><pre><code class="hljs powershell"><span class="hljs-built_in">cd</span> D:\models\baichuan<br>D:\aria2\aria2c.exe <span class="hljs-literal">--all-proxy</span>=<span class="hljs-string">&#x27;http://127.0.0.1:7890&#x27;</span> <span class="hljs-literal">-o</span> <span class="hljs-string">&#x27;pytorch_model.bin&#x27;</span> <span class="hljs-string">&quot;https://huggingface.co/baichuan-inc/Baichuan2-7B-Chat/resolve/main/pytorch_model.bin?download=true&quot;</span><br>conda activate llamaConvert<br>python <span class="hljs-literal">-c</span> <span class="hljs-string">&quot;from huggingface_hub import snapshot_download; snapshot_download(repo_id=&#x27;baichuan-inc/Baichuan2-7B-Chat&#x27;, local_dir=r&#x27;D:\models\baichuan&#x27;, ignore_patterns=[&#x27;*.h5&#x27;, &#x27;*.bin&#x27;, &#x27;*.ot&#x27;, &#x27;*.msgpack&#x27;, &#x27;*.safetensors&#x27;])&quot;</span><br><span class="hljs-built_in">cd</span> D:\llama\llama.cpp<br>python convert.py D:\models\baichuan<br><span class="hljs-comment"># Wrote D:\models\baichuan\ggml-model-f16.gguf</span><br>conda activate llamaCpp<br><span class="hljs-built_in">cd</span> D:\llama ; .\quantize.exe <span class="hljs-literal">--help</span><br>.\quantize.exe D:\models\baichuan\ggml<span class="hljs-literal">-model-f16</span>.gguf .\baichuan<span class="hljs-literal">-7b-Q3_K_M</span>.gguf Q3_K_M<br>.\server.exe <span class="hljs-literal">-m</span> .\baichuan<span class="hljs-literal">-7b-Q3_K_M</span>.gguf <span class="hljs-literal">-c</span> <span class="hljs-number">2048</span> <span class="hljs-literal">--n-gpu-layers</span> <span class="hljs-number">30</span><br></code></pre></td></tr></table></figure>
<h2 id="附加-tigerbot-13b">附加 tigerbot-13b</h2>
<p><a href="https://hexo.limour.top/go/#aHR0cHM6Ly9odWdnaW5nZmFjZS5jby9UaWdlclJlc2VhcmNoL3RpZ2VyYm90LTEzYi1jaGF0LXY1" rel="noopener external nofollow noreferrer">tigerbot-13b</a> 在 <a href="https://hexo.limour.top/go/#aHR0cHM6Ly9naXRodWIuY29tL2plaW5sZWUxOTkxL2NoaW5lc2UtbGxtLWJlbmNobWFyaw==" rel="noopener external nofollow noreferrer">chinese-llm-benchmark</a> 上排名靠前。</p>
<figure class="highlight powershell"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br></pre></td><td class="code"><pre><code class="hljs powershell"><span class="hljs-built_in">cd</span> D:\models\tigerbot<br>D:\aria2\aria2c.exe <span class="hljs-literal">--all-proxy</span>=<span class="hljs-string">&#x27;http://127.0.0.1:7890&#x27;</span> <span class="hljs-literal">-o</span> <span class="hljs-string">&#x27;pytorch_model-00001-of-00003.bin&#x27;</span> <span class="hljs-literal">--max-download-limit</span>=<span class="hljs-number">6</span>M <span class="hljs-string">&quot;https://huggingface.co/TigerResearch/tigerbot-13b-chat-v5/resolve/main/pytorch_model-00001-of-00003.bin?download=true&quot;</span><br>D:\aria2\aria2c.exe <span class="hljs-literal">--all-proxy</span>=<span class="hljs-string">&#x27;http://127.0.0.1:7890&#x27;</span> <span class="hljs-literal">-o</span> <span class="hljs-string">&#x27;pytorch_model-00002-of-00003.bin&#x27;</span> <span class="hljs-literal">--max-download-limit</span>=<span class="hljs-number">6</span>M <span class="hljs-string">&quot;https://huggingface.co/TigerResearch/tigerbot-13b-chat-v5/resolve/main/pytorch_model-00002-of-00003.bin?download=true&quot;</span><br>D:\aria2\aria2c.exe <span class="hljs-literal">--all-proxy</span>=<span class="hljs-string">&#x27;http://127.0.0.1:7890&#x27;</span> <span class="hljs-literal">-o</span> <span class="hljs-string">&#x27;pytorch_model-00003-of-00003.bin&#x27;</span> <span class="hljs-literal">--max-download-limit</span>=<span class="hljs-number">6</span>M <span class="hljs-string">&quot;https://huggingface.co/TigerResearch/tigerbot-13b-chat-v5/resolve/main/pytorch_model-00003-of-00003.bin?download=true&quot;</span><br>conda activate llamaConvert<br>python <span class="hljs-literal">-c</span> <span class="hljs-string">&quot;from huggingface_hub import snapshot_download; snapshot_download(repo_id=&#x27;TigerResearch/tigerbot-13b-chat-v5&#x27;, local_dir=r&#x27;D:\models\tigerbot&#x27;, ignore_patterns=[&#x27;*.h5&#x27;, &#x27;*.bin&#x27;, &#x27;*.ot&#x27;, &#x27;*.msgpack&#x27;, &#x27;*.safetensors&#x27;])&quot;</span><br><span class="hljs-built_in">cd</span> D:\llama\llama.cpp<br>python convert.py D:\models\tigerbot <span class="hljs-literal">--padvocab</span><br><span class="hljs-built_in">cd</span> D:\llama ; .\quantize.exe <span class="hljs-literal">--help</span><br>.\quantize.exe D:\models\tigerbot\ggml<span class="hljs-literal">-model-f16</span>.gguf D:\models\tigerbot<span class="hljs-literal">-13B-Chat-Q4_K_M</span>.gguf Q4_K_M<br>.\server.exe <span class="hljs-literal">-m</span> D:\models\tigerbot<span class="hljs-literal">-13B-Chat-Q4_K_M</span>.gguf <span class="hljs-literal">-c</span> <span class="hljs-number">4096</span><br></code></pre></td></tr></table></figure>
<div class="note note-info">
            <p>感觉 6G 显存下，比较好用的是 Yi-6B-Chat-Q4_K_M<br>tigerbot-13b 在 R5 5600H 上推理速度 4.6 tokens/s，CPU 使用率 60%，频率 3.5GHz，应该是内存带宽瓶颈</p>
          </div>
<h2 id="附加-在-Colab-上量化">附加 在 Colab 上量化</h2>
<ul>
<li><a href="https://hexo.limour.top/go/#aHR0cHM6Ly9jb2xhYi5yZXNlYXJjaC5nb29nbGUuY29tL2RyaXZlLzFKVDNYRmpEN0NUUkI5N3B1M1FwZUd1eldBMXlZRUFNNz91c3A9c2hhcmluZw==" rel="noopener external nofollow noreferrer">llm2gguf.ipynb</a></li>
<li><a href="https://hexo.limour.top/go/#aHR0cHM6Ly9odWdnaW5nZmFjZS5jby9MaW1vdXIvQ2F1c2FsTE0tMTRCLUdHVUY=" rel="noopener external nofollow noreferrer">量化后的结果</a></li>
</ul>
<h3 id="安装-llama-cpp">安装 llama.cpp</h3>
<figure class="highlight ipython"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br></pre></td><td class="code"><pre><code class="hljs ipython">!git clone --depth=<span class="hljs-number">1</span> https://github.com/ggerganov/llama.cpp.git<br>%cd /content/llama.cpp<br>!LLAMA_CUDA=<span class="hljs-number">1</span> make -j<br></code></pre></td></tr></table></figure>
<h3 id="计算-imatrix">计算 imatrix</h3>
<figure class="highlight ipython"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br></pre></td><td class="code"><pre><code class="hljs ipython">%cd /content<br>!wget -O transient.txt.gz https://huggingface.co/datasets/Limour/b-corpus/resolve/main/<span class="hljs-number">00</span>-preview/<span class="hljs-number">00</span>-transient.txt.gz?download=true<br>!gunzip transient.txt.gz<br>!mkdir -p /content/CausalLM-14B-GGUF<br>!wget -O /content/CausalLM-14B-GGUF/causallm_14b.Q8_0.gguf  https://huggingface.co/TheBloke/CausalLM-14B-GGUF/resolve/main/causallm_14b.Q8_0.gguf?download=true<br>!/content/llama.cpp/imatrix -m /content/CausalLM-14B-GGUF/causallm_14b.Q8_0.gguf -f /content/transient.txt -ngl <span class="hljs-number">36</span><br></code></pre></td></tr></table></figure>
<h3 id="登录拥抱脸">登录拥抱脸</h3>
<figure class="highlight ipython"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br></pre></td><td class="code"><pre><code class="hljs ipython"><span class="hljs-keyword">from</span> google.colab <span class="hljs-keyword">import</span> userdata<br><span class="hljs-keyword">from</span> huggingface_hub <span class="hljs-keyword">import</span> login<br><span class="hljs-comment"># login(token=os.environ.get(&quot;HF_TOKEN&quot;), write_permission=True)</span><br>login(token=userdata.get(<span class="hljs-string">&#x27;HF_TOKEN&#x27;</span>), write_permission=<span class="hljs-literal">True</span>)<br><span class="hljs-comment"># from huggingface_hub import notebook_login</span><br><span class="hljs-comment"># notebook_login()</span><br></code></pre></td></tr></table></figure>
<h3 id="跳过-转换模型">(跳过) 转换模型</h3>
<figure class="highlight ipython"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br></pre></td><td class="code"><pre><code class="hljs ipython">%cd llama.cpp<br>!python -m pip install -r requirements.txt<br>!pip install tiktoken<br><span class="hljs-keyword">from</span> huggingface_hub <span class="hljs-keyword">import</span> snapshot_download<br>!mkdir -p ~/CausalLM<br>snapshot_download(repo_id=<span class="hljs-string">&#x27;CausalLM/7B&#x27;</span>, local_dir=<span class="hljs-string">r&#x27;/content/CausalLM&#x27;</span>, ignore_patterns=[<span class="hljs-string">&#x27;*.h5&#x27;</span>, <span class="hljs-string">&#x27;*.ot&#x27;</span>, <span class="hljs-string">&#x27;*.msgpack&#x27;</span>, <span class="hljs-string">&#x27;*.safetensors&#x27;</span>])<br>!python convert.py --vocab-<span class="hljs-built_in">type</span> bpe --pad-vocab --outtype f16 /content/CausalLM <br></code></pre></td></tr></table></figure>
<h3 id="量化模型">量化模型</h3>
<figure class="highlight ipython"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><code class="hljs ipython">!/content/llama.cpp/quantize --allow-requantize --imatrix /content/imatrix.dat /content/CausalLM-14B-GGUF/causallm_14b.Q8_0.gguf /content/CausalLM-14B-GGUF/causallm_14b.IQ3_XS.gguf IQ3_XS<br></code></pre></td></tr></table></figure>
<h3 id="上传模型">上传模型</h3>
<figure class="highlight ipython"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br></pre></td><td class="code"><pre><code class="hljs ipython"><span class="hljs-keyword">from</span> huggingface_hub <span class="hljs-keyword">import</span> HfApi<br>api = HfApi()<br>api.upload_file(<br>    path_or_fileobj=<span class="hljs-string">&quot;/content/CausalLM-14B-GGUF/causallm_14b.IQ3_XS.gguf&quot;</span>,<br>    path_in_repo=<span class="hljs-string">&quot;causallm_14b.IQ3_XS.gguf&quot;</span>,<br>    repo_id=<span class="hljs-string">&quot;Limour/CausalLM-14B-GGUF&quot;</span><br>)<br></code></pre></td></tr></table></figure>
                
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