Update - Other quants from other authors get flagged as well:
https://huggingface.co/mradermacher/c4ai-command-r7b-12-2024-i1-GGUF
https://huggingface.co/mmnga/c4ai-command-r7b-12-2024-gguf
Some are not flagged (yet) because the files are being queued to be scanned (bartowski's quants for example).
Anyway, maybe it's a false positive, but just to be sure, don't download if you feel like it's a risk.
Note: you will need llama.cpp
b4415 or later to run the model.
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code. The model is trained to perform sophisticated tasks including Retrieval Augmented Generation (RAG) and tool use. The model also has powerful agentic capabilities with the ability to use and combine multiple tools over multiple steps to accomplish more difficult tasks. It obtains top performance on enterprise relevant code use cases. C4AI Command R7B is a multilingual model trained on 23 languages.
You can try out C4AI Command R7B before downloading the weights in our hosted
Hugging Face Space.
Please install transformers from the source repository that includes the necessary changes for this model.
1# pip install 'git+https://github.com/huggingface/transformers.git'
2from transformers import AutoTokenizer, AutoModelForCausalLM
3
4model_id = "CohereForAI/c4ai-command-r7b-12-2024"
5tokenizer = AutoTokenizer.from_pretrained(model_id)
6model = AutoModelForCausalLM.from_pretrained(model_id)
7
8# Format message with the c4ai-command-r7b-12-2024 chat template
9messages = [{"role": "user", "content": "Hello, how are you?"}]
10input_ids = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt")
11
12gen_tokens = model.generate(
13 input_ids,
14 max_new_tokens=100,
15 do_sample=True,
16 temperature=0.3,
17)
18
19gen_text = tokenizer.decode(gen_tokens[0], skip_special_tokens=True)
20print(gen_text)