Instructions to use Linly-AI/Chinese-Falcon-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Linly-AI/Chinese-Falcon-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Linly-AI/Chinese-Falcon-7B", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Linly-AI/Chinese-Falcon-7B", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Linly-AI/Chinese-Falcon-7B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Linly-AI/Chinese-Falcon-7B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Linly-AI/Chinese-Falcon-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Linly-AI/Chinese-Falcon-7B
- SGLang
How to use Linly-AI/Chinese-Falcon-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 "Linly-AI/Chinese-Falcon-7B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Linly-AI/Chinese-Falcon-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "Linly-AI/Chinese-Falcon-7B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Linly-AI/Chinese-Falcon-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Linly-AI/Chinese-Falcon-7B with Docker Model Runner:
docker model run hf.co/Linly-AI/Chinese-Falcon-7B
Upload 5 files
Browse files- pytorch_model-00002-of-00002.bin +3 -0
- pytorch_model.bin.index.json +1 -0
- special_tokens_map.json +16 -0
- tokenizer.json +0 -0
- tokenizer_config.json +7 -0
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"transformer.h.9.self_attention.query_key_value.weight": "pytorch_model-00001-of-00002.bin", "transformer.ln_f.bias": "pytorch_model-00002-of-00002.bin", "transformer.ln_f.weight": "pytorch_model-00002-of-00002.bin", "transformer.word_embeddings.weight": "pytorch_model-00001-of-00002.bin"}}
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special_tokens_map.json
ADDED
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+
{
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+
"additional_special_tokens": [
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| 3 |
+
">>TITLE<<",
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| 4 |
+
">>ABSTRACT<<",
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| 5 |
+
">>INTRODUCTION<<",
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| 6 |
+
">>SUMMARY<<",
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| 7 |
+
">>COMMENT<<",
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| 8 |
+
">>ANSWER<<",
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| 9 |
+
">>QUESTION<<",
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| 10 |
+
">>DOMAIN<<",
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| 11 |
+
">>PREFIX<<",
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| 12 |
+
">>SUFFIX<<",
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| 13 |
+
">>MIDDLE<<"
|
| 14 |
+
],
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| 15 |
+
"eos_token": "<|endoftext|>"
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| 16 |
+
}
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tokenizer.json
ADDED
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tokenizer_config.json
ADDED
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+
{
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| 2 |
+
"add_prefix_space": false,
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| 3 |
+
"clean_up_tokenization_spaces": true,
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| 4 |
+
"eos_token": "<|endoftext|>",
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| 5 |
+
"model_max_length": 2048,
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| 6 |
+
"tokenizer_class": "PreTrainedTokenizerFast"
|
| 7 |
+
}
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