Instructions to use TheBloke/Llama-2-7B-Chat-GGML with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheBloke/Llama-2-7B-Chat-GGML with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TheBloke/Llama-2-7B-Chat-GGML")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TheBloke/Llama-2-7B-Chat-GGML", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use TheBloke/Llama-2-7B-Chat-GGML with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TheBloke/Llama-2-7B-Chat-GGML" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TheBloke/Llama-2-7B-Chat-GGML", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/TheBloke/Llama-2-7B-Chat-GGML
- SGLang
How to use TheBloke/Llama-2-7B-Chat-GGML with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "TheBloke/Llama-2-7B-Chat-GGML" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TheBloke/Llama-2-7B-Chat-GGML", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "TheBloke/Llama-2-7B-Chat-GGML" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TheBloke/Llama-2-7B-Chat-GGML", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use TheBloke/Llama-2-7B-Chat-GGML with Docker Model Runner:
docker model run hf.co/TheBloke/Llama-2-7B-Chat-GGML
Tokenizer behaving differently than Meta's original.
I'm having a issue while decoding/encoding.
This is also related to the chat completion format already mentioned previously in other discussions.
You can see the issue in details and also replicate it here. I'm comparing Meta original tokenizer with this model using llama-cpp-python.
In summary, the tokens 518 and 29961 are being decoded/encoded differently.
As I think we discussed on my Discord, there's nothing I can do about this as I used the correct tokenizer.model and that is the output that was produced. Have you discussed it on the llama.cpp Github?
Yes, I'm trying to get this conversation on the llama.cpp repo. Thank you very much!