Comments (6)
所以这样是出现问题吗?当我在部署模型的时候,链接服务就停在这里,一直动不了,但是不知道为什么,(禁用了GPU)
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这样是成功启动了的。动不了的问题我观察可能是vscode的插件有问题吧,这个很慢才但会响应,目前发现只有chat能用,自动补全完全没效果。
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同样存在编译后运行错误的问题,错误信息如下
llm_load_print_meta: format = GGUF V2 (latest)
llm_load_print_meta: arch = codeshell
llm_load_print_meta: vocab type = BPE
llm_load_print_meta: n_vocab = 70144
llm_load_print_meta: n_merges = 72075
llm_load_print_meta: n_ctx_train = 8192
llm_load_print_meta: n_embd = 4096
llm_load_print_meta: n_head = 32
llm_load_print_meta: n_head_kv = 8
llm_load_print_meta: n_layer = 42
llm_load_print_meta: n_rot = 128
llm_load_print_meta: n_gqa = 4
llm_load_print_meta: f_norm_eps = 1.0e-05
llm_load_print_meta: f_norm_rms_eps = 0.0e+00
llm_load_print_meta: f_clamp_kqv = 0.0e+00
llm_load_print_meta: f_max_alibi_bias = 0.0e+00
llm_load_print_meta: n_ff = 16384
llm_load_print_meta: freq_base_train = 10000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: model type = 7B
llm_load_print_meta: model ftype = mostly Q4_0
llm_load_print_meta: model params = 7.98 B
llm_load_print_meta: model size = 4.25 GiB (4.58 BPW)
llm_load_print_meta: general.name = CodeShell
llm_load_print_meta: BOS token = 70000 '<|endoftext|>'
llm_load_print_meta: EOS token = 70000 '<|endoftext|>'
llm_load_print_meta: UNK token = 70000 '<|endoftext|>'
llm_load_print_meta: PAD token = 70000 '<|endoftext|>'
llm_load_print_meta: LF token = 28544 'ÄĬ'
llm_load_tensors: ggml ctx size = 0.17 MB
llm_load_tensors: using CUDA for GPU acceleration
llm_load_tensors: mem required = 154.30 MB
llm_load_tensors: offloading 42 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 45/45 layers to GPU
llm_load_tensors: VRAM used: 4201.34 MB
.GGML_ASSERT: ggml-cuda.cu:6115: false
Aborted (core dumped)
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这样是成功启动了的。动不了的问题我观察可能是vscode的插件有问题吧,这个很慢才但会响应,目前发现只有chat能用,自动补全完全没效果。
现在我和你情况完全一样
from codeshell-vscode.
这样是成功启动了的。动不了的问题我观察可能是vscode的插件有问题吧,这个很慢才但会响应,目前发现只有chat能用,自动补全完全没效果。
cpu 模式下自动补全非常慢,还是能够成功出现自动补全结果的
from codeshell-vscode.
这样是成功启动了的。动不了的问题我观察可能是vscode的插件有问题吧,这个很慢才但会响应,目前发现只有chat能用,自动补全完全没效果。
- 目前自动补全功能已完善,已更新了server和插件。请参考README,更新本地的llama_cpp_for_codeshell,重新make,并更新插件。
- CPU运行大模型确实很慢,建议使用GPU或者M1/M2芯片及以上的Mac。
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Related Issues (20)
- 是否考虑 用template 来向LLM 提问? HOT 2
- 启动TGI报错
- GPU方式运行模型服务出错 HOT 3
- -ngl 0 不加触发自动补齐服务就挂了,加了得10s+才能出来 HOT 4
- 回答问题后输出无法自动停止 HOT 1
- Docker启动量化模型的GPU模式 HOT 2
- FetchError:request to http://127.0.0.1:8080/completionfailed HOT 2
- 可以把 codeshell-chat-q4_0.gguf 往魔搭社区传一份吗? HOT 2
- Is is support deepseek coder yet ? HOT 2
- RAG+Langchain to make its more powerful?
- 检查性能问题,跟检查安全问题的prompts函数混淆了 HOT 1
- 魔搭4it模型中缺codeshell-chat-q4_0.gguf HOT 2
- 插件中访问模型url添加后缀completion,模型那边部署是completions HOT 2
- docker run --gpus 'all' 报错,多卡不支持吗 HOT 1
- 模型服务启动后网页能正常访问,但是vscode插件访问时服务端提示404异常?
- code-server安装codeshell-vscode插件对话框空白 HOT 1
- 有没有在windows上本地部署(用GPU、不用docker)的办法
- unable to load model
- codeshll不支持shared吗
- codeshell支持idea的插件有开源吗? 怎么没有看到地址
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