Instructions to use codeaze/CA-Pharma-Mistral-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codeaze/CA-Pharma-Mistral-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="codeaze/CA-Pharma-Mistral-7B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("codeaze/CA-Pharma-Mistral-7B") model = AutoModelForCausalLM.from_pretrained("codeaze/CA-Pharma-Mistral-7B") 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 codeaze/CA-Pharma-Mistral-7B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "codeaze/CA-Pharma-Mistral-7B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "codeaze/CA-Pharma-Mistral-7B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/codeaze/CA-Pharma-Mistral-7B
- SGLang
How to use codeaze/CA-Pharma-Mistral-7B 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 "codeaze/CA-Pharma-Mistral-7B" \ --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": "codeaze/CA-Pharma-Mistral-7B", "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 "codeaze/CA-Pharma-Mistral-7B" \ --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": "codeaze/CA-Pharma-Mistral-7B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use codeaze/CA-Pharma-Mistral-7B with Docker Model Runner:
docker model run hf.co/codeaze/CA-Pharma-Mistral-7B
Upload tokenizer
Browse files- special_tokens_map.json +1 -1
- tokenizer.json +18 -0
- tokenizer_config.json +21 -3
special_tokens_map.json
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"single_word": false
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},
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"eos_token": {
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"content": "<
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "<|im_end|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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tokenizer.json
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"rstrip": false,
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"normalized": false,
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"special": true
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"normalizer": {
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"rstrip": false,
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"normalized": false,
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"special": true
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},
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{
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"id": 32000,
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"content": "<|im_end|>",
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"single_word": false,
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"lstrip": false,
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"rstrip": false,
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"normalized": false,
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"special": true
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},
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{
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"id": 32001,
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"content": "<|im_start|>",
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"single_word": false,
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"lstrip": false,
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"rstrip": false,
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"normalized": false,
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"special": true
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}
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],
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"normalizer": {
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tokenizer_config.json
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"additional_special_tokens": [],
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"bos_token": "<s>",
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"chat_template": "{
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"clean_up_tokenization_spaces": false,
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"eos_token": "<
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"legacy": true,
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": null,
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"sp_model_kwargs": {},
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"spaces_between_special_tokens": false,
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"tokenizer_class": "LlamaTokenizer",
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"unk_token": "<unk>",
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"use_default_system_prompt":
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}
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"32000": {
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"content": "<|im_end|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"32001": {
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"content": "<|im_start|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"additional_special_tokens": [],
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"bos_token": "<s>",
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"chat_template": "{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
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"clean_up_tokenization_spaces": false,
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"eos_token": "<|im_end|>",
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"legacy": true,
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": null,
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"sp_model_kwargs": {},
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"spaces_between_special_tokens": false,
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"tokenizer_class": "LlamaTokenizer",
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"trust_remote_code": false,
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"unk_token": "<unk>",
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"use_default_system_prompt": true,
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"use_fast": true
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}
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