Try writing up the huggingface model directory instead of the bin file. But this is only supported on some architectures. FROM C:\ollama_models\florence-2-base\ https://github.com/ollama/ollama/blob/main/docs/import.md#automatic-quantization Author javierxio commented Jun 24, 2024 @mili-...
and got satisfying results in inference, but when i try to use SFTTrainer.save_model, and load the model from the saved files using LlamaForCausalLM.from_pretrained, the inference result seem to just be of the not fine-tuned model
To run a Hugging Face model, do the following: 1 2 3 4 5 6 public void createImage(String imageName, String repository, String model) { var model = new OllamaHuggingFaceContainer.HuggingFaceModel(repository, model); var huggingFaceContainer = new OllamaHuggingFaceContainer(hfModel); hug...
You should download the model by cloning the repository and tokenizer weights manually to run it offline. You can find more information on how to run Transformers offline on the HuggingFace documentation: https://transformers.huggingface.co/docs/usage/inference#offline-inference Example: #Assuming you...
pip install torchvision torchaudio torch--index-url https://download.pytorch.org/whl/cu118 5.Run the following python code: fromtransformersimportAutoModelForCausalLM,AutoTokenizer# Load the model and tokenizermodel_name="meta-llama/Llama-2-7b-chat-hf"model...
7 ./main -m$LLAMA_MODEL_LOCATION/ggml-model-f16.gguf -n -1 --ignore-eos -t4--mlock --no-mmap --color -i -r"User:"-f prompts/chat-with-bob.txt# run the model in prompt modesudo taskset -c 4,5,6,7 ./main -m$LLAMA_MODEL_LOCATION/ggml-model-f16.gguf --ignore-eos -...
In the example above, we are using text-ada-001 model from OpenAI. If you would like to swap that for any open-source models from HuggingFace, it’s a simple change: API_KEY ="..." from langchain import HuggingFaceHub llm = HuggingFaceHub(repo_id = "google/flan-t5-xl", huggingface...
4. Llamafile Llamafile, developed by Mozilla, offers a user-friendly alternative for running LLMs. Llamafile is known for its portability and the ability to create single-file executables. Once we download llamafile and any GGUF-formatted model, we can start a local browser session with: ...
We will use LangChain to create a sample RAG application and the RAGAS framework for evaluation. RAGAS is open-source, has out-of-the-box support for all the above metrics, supports custom evaluation prompts, and has integrations with frameworks such as LangChain, LlamaIndex, and observability...
To install all the packages simultaneously from the requirements file run this command on your terminal. pip install -r requirements.txt Great. Now we can start coding! 👨💻 I want to instantiate the tiny-llama-1B model. The model and themodel cardcan be easily found onHuggingFace(HF...