Instructions to use BSC-LT/salamandraTA-7B-instruct-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BSC-LT/salamandraTA-7B-instruct-GGUF with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="BSC-LT/salamandraTA-7B-instruct-GGUF") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("BSC-LT/salamandraTA-7B-instruct-GGUF") model = AutoModelForMultimodalLM.from_pretrained("BSC-LT/salamandraTA-7B-instruct-GGUF") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - llama-cpp-python
How to use BSC-LT/salamandraTA-7B-instruct-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="BSC-LT/salamandraTA-7B-instruct-GGUF", filename="salamandraTA_7B_inst_q4.gguf", )
llm.create_chat_completion( messages = "\"Меня зовут Вольфганг и я живу в Берлине\"" )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use BSC-LT/salamandraTA-7B-instruct-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf BSC-LT/salamandraTA-7B-instruct-GGUF # Run inference directly in the terminal: llama-cli -hf BSC-LT/salamandraTA-7B-instruct-GGUF
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf BSC-LT/salamandraTA-7B-instruct-GGUF # Run inference directly in the terminal: llama-cli -hf BSC-LT/salamandraTA-7B-instruct-GGUF
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 BSC-LT/salamandraTA-7B-instruct-GGUF # Run inference directly in the terminal: ./llama-cli -hf BSC-LT/salamandraTA-7B-instruct-GGUF
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 BSC-LT/salamandraTA-7B-instruct-GGUF # Run inference directly in the terminal: ./build/bin/llama-cli -hf BSC-LT/salamandraTA-7B-instruct-GGUF
Use Docker
docker model run hf.co/BSC-LT/salamandraTA-7B-instruct-GGUF
- LM Studio
- Jan
- Ollama
How to use BSC-LT/salamandraTA-7B-instruct-GGUF with Ollama:
ollama run hf.co/BSC-LT/salamandraTA-7B-instruct-GGUF
- Unsloth Studio
How to use BSC-LT/salamandraTA-7B-instruct-GGUF 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 BSC-LT/salamandraTA-7B-instruct-GGUF 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 BSC-LT/salamandraTA-7B-instruct-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for BSC-LT/salamandraTA-7B-instruct-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use BSC-LT/salamandraTA-7B-instruct-GGUF with Docker Model Runner:
docker model run hf.co/BSC-LT/salamandraTA-7B-instruct-GGUF
- Lemonade
How to use BSC-LT/salamandraTA-7B-instruct-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull BSC-LT/salamandraTA-7B-instruct-GGUF
Run and chat with the model
lemonade run user.salamandraTA-7B-instruct-GGUF-{{QUANT_TAG}}List all available models
lemonade list
Two weights but same filename?
It seems like there are two files with the same filename, except the "ta" is turned into "TA" for the latest one (updated ~1 week ago). It seems to me like they're two different versions, so maybe it would be appropriate to add a version suffix or similar? Or since it's a git repository, just straight up replace the file with the newest.
Hello,
Thank you for your comment.
As you said, the new file is an update of the original one. We removed the old one to avoid further issues.
Best regards,
Carlos
Hi!
Maybe you could change:
model_name = "salamandrata_7b_inst_q4.gguf"
in the "How to use section" to
model_name = "salamandraTA_7b_inst_q4.gguf"
right now it raises an error regarding the initialization of the model.
Best regards,
Mauro
