Text Generation
Transformers
Safetensors
GGUF
English
Spanish
French
llama
Merge
text-generation-inference
conversational
Instructions to use appvoid/palmer-003 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use appvoid/palmer-003 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="appvoid/palmer-003") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("appvoid/palmer-003") model = AutoModelForCausalLM.from_pretrained("appvoid/palmer-003") - llama-cpp-python
How to use appvoid/palmer-003 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="appvoid/palmer-003", filename="palmer-003.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use appvoid/palmer-003 with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf appvoid/palmer-003 # Run inference directly in the terminal: llama-cli -hf appvoid/palmer-003
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf appvoid/palmer-003 # Run inference directly in the terminal: llama-cli -hf appvoid/palmer-003
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf appvoid/palmer-003 # Run inference directly in the terminal: ./llama-cli -hf appvoid/palmer-003
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf appvoid/palmer-003 # Run inference directly in the terminal: ./build/bin/llama-cli -hf appvoid/palmer-003
Use Docker
docker model run hf.co/appvoid/palmer-003
- LM Studio
- Jan
- vLLM
How to use appvoid/palmer-003 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "appvoid/palmer-003" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "appvoid/palmer-003", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/appvoid/palmer-003
- SGLang
How to use appvoid/palmer-003 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 "appvoid/palmer-003" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "appvoid/palmer-003", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "appvoid/palmer-003" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "appvoid/palmer-003", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use appvoid/palmer-003 with Ollama:
ollama run hf.co/appvoid/palmer-003
- Unsloth Studio new
How to use appvoid/palmer-003 with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for appvoid/palmer-003 to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for appvoid/palmer-003 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for appvoid/palmer-003 to start chatting
- Docker Model Runner
How to use appvoid/palmer-003 with Docker Model Runner:
docker model run hf.co/appvoid/palmer-003
- Lemonade
How to use appvoid/palmer-003 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull appvoid/palmer-003
Run and chat with the model
lemonade run user.palmer-003-{{QUANT_TAG}}List all available models
lemonade list
Adding ONNX file of this model
#1
by appvoid - opened
- .gitattributes +1 -0
- README.md +1 -0
- onnx/config.json +31 -0
- onnx/generation_config.json +6 -0
- onnx/model.onnx +3 -0
- onnx/model.onnx_data +3 -0
- onnx/special_tokens_map.json +30 -0
- onnx/tokenizer.json +0 -0
- onnx/tokenizer_config.json +43 -0
.gitattributes
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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palmer-003.gguf filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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palmer-003.gguf filter=lfs diff=lfs merge=lfs -text
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onnx/model.onnx_data filter=lfs diff=lfs merge=lfs -text
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README.md
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tags:
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- merge
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---
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tags:
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- onnx
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---
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onnx/config.json
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{
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"_attn_implementation_autoset": true,
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"architectures": [
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"LlamaForCausalLM"
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"attention_bias": false,
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"head_dim": 64,
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"hidden_act": "silu",
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"hidden_size": 2048,
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"intermediate_size": 5632,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 22,
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"num_key_value_heads": 4,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 10000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "float32",
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"transformers_version": "4.51.3",
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"unsloth_version": "2024.1",
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"use_cache": false,
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"vocab_size": 32000
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}
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{
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"eos_token_id": 2,
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"transformers_version": "4.51.3"
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}
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onnx/model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:303b0b993bc1e8ee6ca388b7baf98e2818b5448bb9d7cf2076e8b3d36c21f8b3
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size 979599
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onnx/model.onnx_data
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version https://git-lfs.github.com/spec/v1
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size 4400193536
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onnx/special_tokens_map.json
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{
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}
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onnx/tokenizer.json
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onnx/tokenizer_config.json
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{
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"bos_token": "<s>",
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"clean_up_tokenization_spaces": false,
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"eos_token": "</s>",
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"extra_special_tokens": {},
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"pad_token": "</s>",
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| 38 |
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"sp_model_kwargs": {},
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"tokenizer_class": "LlamaTokenizer",
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"unk_token": "<unk>",
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"use_default_system_prompt": false
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}
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