git clone https://github.com/ggerganov/llama.cpp cd llama.cpp mkdir build # I use make method because the token generating speed is faster than cmake method. # (Optional) MPI build make CC=mpicc CXX=mpicxx LLAMA_MPI=1 # (Optional) OpenBLAS build make LLAMA_OPENBLAS=1 # (Optional) ...
In the space of local LLMs, I first ran into LMStudio. While the app itself is easy to use, I liked the simplicity and maneuverability that Ollama provides.
This endpoint generates a response to a simple text prompt. It’s straightforward and doesn’t involve a conversation context. Use this when you need a single, standalone output based on your input. Example: # Define the prompt and parameterspayload={"model":"your-model-name",# Replace with...
cog run python -m transformers.models.llama.convert_llama_weights_to_hf \ --input_dir unconverted-weights \ --model_size 7B \ --output_dir weights You final directory structure should look like this: weights ├── llama-7b └── tokenizermdki Step 4: Fine-tune the model The fine-tuni...
gpt4=ChatOpenAI(model="gpt-4"), # You can add more configuration options here ) prompt = PromptTemplate.from_template("Tell me a joke about {topic}") chain = prompt | llm # 可以利用`.with_config(configurable={"llm": "openai"})` to specify an llm to use ...
In your app directory, create a new file called Dockerfile. nano Dockerfile Paste the following code into the Dockerfile: FROM serge-chat/serge:latest COPY my-model.pkl /app/ CMD ["python", "app.py"] This Dockerfile tells Docker to use the latest version of the Serge image as the ba...
Question Validation I have searched both the documentation and discord for an answer. Question I'm using llama_index on chroma ,but there is still a question. According to the example:[Chroma - LlamaIndex 🦙 0.7.22 (gpt-index.readthedocs...
In this section, you use theAzure AI model inference APIwith a chat completions model for chat. 提示 TheAzure AI model inference APIallows you to talk with most models deployed in Azure AI Studio with the same code and structure, including Meta Llama chat models. ...
In this section, you use the Azure AI model inference API with a chat completions model for chat. 提示 The Azure AI model inference API allows you to talk with most models deployed in Azure AI Foundry portal with the same code and structure, including Phi-3.5 chat model wit...
The Llama 3.2 lightweight models (1B and 3B) were built to fit efficiently on mobile and edge devices while maintaining strong performance. To achieve this, Meta used two key techniques: pruning and distillation. Source: Meta AI Pruning: Making the model smaller Pruning helps reduce the size ...