Instructions to use jackboot/quill-57b-tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jackboot/quill-57b-tokenizer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="jackboot/quill-57b-tokenizer") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("jackboot/quill-57b-tokenizer") model = AutoModelForCausalLM.from_pretrained("jackboot/quill-57b-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 jackboot/quill-57b-tokenizer with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "jackboot/quill-57b-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": "jackboot/quill-57b-tokenizer", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/jackboot/quill-57b-tokenizer
- SGLang
How to use jackboot/quill-57b-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 "jackboot/quill-57b-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": "jackboot/quill-57b-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 "jackboot/quill-57b-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": "jackboot/quill-57b-tokenizer", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use jackboot/quill-57b-tokenizer with Docker Model Runner:
docker model run hf.co/jackboot/quill-57b-tokenizer
gguf is broken
Browse filessomeone might need these as I need the 72b ones
- config.json +35 -0
- configuration.json +5 -0
- generation_config.json +9 -0
- special_tokens_map.json +16 -0
- tokenizer.json +0 -0
- tokenizer_config.json +41 -0
- vocab.json +0 -0
config.json
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{
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"architectures": [
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"Qwen2MoeForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 151643,
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"decoder_sparse_step": 1,
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"eos_token_id": 151643,
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"hidden_act": "silu",
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"hidden_size": 3584,
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"initializer_range": 0.02,
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"intermediate_size": 18944,
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"max_position_embeddings": 131072,
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"max_window_layers": 21,
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"model_type": "qwen2_moe",
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"moe_intermediate_size": 2560,
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"norm_topk_prob": false,
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"num_attention_heads": 28,
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"num_experts": 64,
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"num_experts_per_tok": 8,
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"num_hidden_layers": 28,
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"num_key_value_heads": 4,
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"output_router_logits": false,
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"rms_norm_eps": 1e-06,
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"rope_theta": 1000000.0,
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"router_aux_loss_coef": 0.001,
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"shared_expert_intermediate_size": 20480,
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"sliding_window": 4096,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.40.1",
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"use_cache": true,
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"use_sliding_window": false,
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"vocab_size": 151936
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}
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configuration.json
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{
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"framework": "pytorch",
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"task": "fill-mask",
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"allow_remote": true
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}
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generation_config.json
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{
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"bos_token_id": 151643,
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"pad_token_id": 151643,
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"eos_token_id": [
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151645,
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151643
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],
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"transformers_version": "4.40.0.dev0"
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}
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special_tokens_map.json
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{
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"eos_token": {
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"content": "<|endoftext|>",
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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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"pad_token": {
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"content": "<|endoftext|>",
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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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}
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tokenizer.json
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tokenizer_config.json
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{
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"add_prefix_space": false,
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"added_tokens_decoder": {
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"151643": {
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"content": "<|endoftext|>",
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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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"151644": {
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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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"151645": {
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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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},
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"additional_special_tokens": ["<|im_start|>", "<|im_end|>"],
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"bos_token": null,
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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": "<|endoftext|>",
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"errors": "replace",
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"model_max_length": 32768,
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"pad_token": "<|endoftext|>",
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"split_special_tokens": false,
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"tokenizer_class": "Qwen2Tokenizer",
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"unk_token": null
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}
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vocab.json
ADDED
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The diff for this file is too large to render.
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