C4AI Command R+ 模型卡片

from openmind import AutoTokenizer, AutoModelForCausalLM

model_id = "AI-Research/c4ai-command-r-plus"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)

# Format message with the command-r-plus chat template
messages = [{"role": "user", "content": "Hello, how are you?"}]
input_ids = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt")
## <BOS_TOKEN><|START_OF_TURN_TOKEN|><|USER_TOKEN|>Hello, how are you?<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>

gen_tokens = model.generate(
    input_ids, 
    max_new_tokens=100, 
    do_sample=True, 
    temperature=0.3,
    )

gen_text = tokenizer.decode(gen_tokens[0])
print(gen_text)

from openmind import AutoTokenizer, AutoModelForCausalLM
from transformers import BitsAndBytesConfig

bnb_config = BitsAndBytesConfig(load_in_8bit=True)

model_id = "AI-Research/c4ai-command-r-plus"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, quantization_config=bnb_config)

# Format message with the command-r-plus chat template
messages = [{"role": "user", "content": "Hello, how are you?"}]
input_ids = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt")
## <BOS_TOKEN><|START_OF_TURN_TOKEN|><|USER_TOKEN|>Hello, how are you?<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>

gen_tokens = model.generate(
    input_ids, 
    max_new_tokens=100, 
    do_sample=True, 
    temperature=0.3,
    )

gen_text = tokenizer.decode(gen_tokens[0])
print(gen_text)

from transformers import AutoTokenizer

model_id = "CohereForAI/c4ai-command-r-plus"
tokenizer = AutoTokenizer.from_pretrained(model_id)

# define conversation input:
conversation = [
    {"role": "user", "content": "Whats the biggest penguin in the world?"}
]
# define documents to ground on:
documents = [
    { "title": "Tall penguins", "text": "Emperor penguins are the tallest growing up to 122 cm in height." }, 
    { "title": "Penguin habitats", "text": "Emperor penguins only live in Antarctica."}
]

# render the tool use prompt as a string:
grounded_generation_prompt = tokenizer.apply_grounded_generation_template(
    conversation,
    documents=documents,
    citation_mode="accurate", # or "fast"
    tokenize=False,
    add_generation_prompt=True,
)
print(grounded_generation_prompt)

Relevant Documents: 0,1
Cited Documents: 0,1
Answer: The Emperor Penguin is the tallest or biggest penguin in the world. It is a bird that lives only in Antarctica and grows to a height of around 122 centimetres.
Grounded answer: The <co: 0>Emperor Penguin</co: 0> is the <co: 0>tallest</co: 0> or biggest penguin in the world. It is a bird that <co: 1>lives only in Antarctica</co: 1> and <co: 0>grows to a height of around 122 centimetres.</co: 0>

from transformers import AutoTokenizer

model_id = "CohereForAI/c4ai-command-r-plus"
tokenizer = AutoTokenizer.from_pretrained(model_id)

# define conversation input:
conversation = [
    {"role": "user", "content": "Whats the biggest penguin in the world?"}
]

# Define tools available for the model to use
# Type hints and docstrings from Python functions are automatically extracted
def internet_search(query: str):
    """
    Returns a list of relevant document snippets for a textual query retrieved from the internet

    Args:
        query: Query to search the internet with
    """
    pass

def directly_answer():
    """
    Calls a standard (un-augmented) AI chatbot to generate a response given the conversation history
    """
    pass

tools = [internet_search, directly_answer]

# render the tool use prompt as a string:
tool_use_prompt = tokenizer.apply_chat_template(
    conversation,
    tools=tools,
    tokenize=False,
    add_generation_prompt=True,
)
print(tool_use_prompt)

<BOS_TOKEN><|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|># Safety Preamble
The instructions in this section override those in the task description and style guide sections. Don't answer questions that are harmful or immoral.

# System Preamble
## Basic Rules
You are a powerful conversational AI trained by Cohere to help people. You are augmented by a number of tools, and your job is to use and consume the output of these tools to best help the user. You will see a conversation history between yourself and a user, ending with an utterance from the user. You will then see a specific instruction instructing you what kind of response to generate. When you answer the user's requests, you cite your sources in your answers, according to those instructions.

# User Preamble
## Task and Context
You help people answer their questions and other requests interactively. You will be asked a very wide array of requests on all kinds of topics. You will be equipped with a wide range of search engines or similar tools to help you, which you use to research your answer. You should focus on serving the user's needs as best you can, which will be wide-ranging.

## Style Guide
Unless the user asks for a different style of answer, you should answer in full sentences, using proper grammar and spelling.

## Available Tools
Here is a list of tools that you have available to you:

```python
def internet_search(query: str) -> List[Dict]:
    """Returns a list of relevant document snippets for a textual query retrieved from the internet

    Args:
        query (str): Query to search the internet with
    """
    pass
```

```python
def directly_answer() -> List[Dict]:
    """Calls a standard (un-augmented) AI chatbot to generate a response given the conversation history
    """
    pass
```<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|USER_TOKEN|>Whats the biggest penguin in the world?<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>Write 'Action:' followed by a json-formatted list of actions that you want to perform in order to produce a good response to the user's last input. You can use any of the supplied tools any number of times, but you should aim to execute the minimum number of necessary actions for the input. You should use the `directly-answer` tool if calling the other tools is unnecessary. The list of actions you want to call should be formatted as a list of json objects, for example:
```json
[
    {
        "tool_name": title of the tool in the specification,
        "parameters": a dict of parameters to input into the tool as they are defined in the specs, or {} if it takes no parameters
    }
]```<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>

Action: ```json
[
      {
          "tool_name": "internet_search",
          "parameters": {
              "query": "biggest penguin in the world"
          }
      }
]
```