Instructions to use PJMixers-Archive/CohereForAI_c4ai-command-r-plus-tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use PJMixers-Archive/CohereForAI_c4ai-command-r-plus-tokenizer with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="PJMixers-Archive/CohereForAI_c4ai-command-r-plus-tokenizer")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("PJMixers-Archive/CohereForAI_c4ai-command-r-plus-tokenizer")
model = AutoModelForCausalLM.from_pretrained("PJMixers-Archive/CohereForAI_c4ai-command-r-plus-tokenizer")
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]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use PJMixers-Archive/CohereForAI_c4ai-command-r-plus-tokenizer with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "PJMixers-Archive/CohereForAI_c4ai-command-r-plus-tokenizer"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "PJMixers-Archive/CohereForAI_c4ai-command-r-plus-tokenizer",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/PJMixers-Archive/CohereForAI_c4ai-command-r-plus-tokenizer

SGLang

How to use PJMixers-Archive/CohereForAI_c4ai-command-r-plus-tokenizer 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 "PJMixers-Archive/CohereForAI_c4ai-command-r-plus-tokenizer" \
    --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": "PJMixers-Archive/CohereForAI_c4ai-command-r-plus-tokenizer",
		"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 "PJMixers-Archive/CohereForAI_c4ai-command-r-plus-tokenizer" \
        --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": "PJMixers-Archive/CohereForAI_c4ai-command-r-plus-tokenizer",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use PJMixers-Archive/CohereForAI_c4ai-command-r-plus-tokenizer with Docker Model Runner:
```
docker model run hf.co/PJMixers-Archive/CohereForAI_c4ai-command-r-plus-tokenizer
```

xzuyn commited on Jun 9, 2024

Commit

8644b76

verified ·

1 Parent(s): 75c74ac

Delete config.json

Browse files

Files changed (1) hide show

config.json +0 -28

config.json DELETED Viewed

@@ -1,28 +0,0 @@
-{
-  "architectures": [
-    "CohereForCausalLM"
-  ],
-  "attention_bias": false,
-  "attention_dropout": 0.0,
-  "bos_token_id": 5,
-  "eos_token_id": 255001,
-  "hidden_act": "silu",
-  "hidden_size": 12288,
-  "initializer_range": 0.02,
-  "intermediate_size": 33792,
-  "layer_norm_eps": 1e-05,
-  "logit_scale": 0.8333333333333334,
-  "max_position_embeddings": 8192,
-  "model_max_length": 131072,
-  "model_type": "cohere",
-  "num_attention_heads": 96,
-  "num_hidden_layers": 64,
-  "num_key_value_heads": 8,
-  "pad_token_id": 0,
-  "rope_theta": 75000000.0,
-  "torch_dtype": "float16",
-  "transformers_version": "4.40.0.dev0",
-  "use_cache": true,
-  "use_qk_norm": true,
-  "vocab_size": 256000
-}