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Model: mistralai/Mistral-7B-Instruct-v0.1 Source: Original Platform
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README.md
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---
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library_name: transformers
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license: apache-2.0
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tags:
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- finetuned
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- mistral-common
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base_model: mistralai/Mistral-7B-v0.1
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inference: false
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widget:
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- messages:
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- role: user
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content: What is your favorite condiment?
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extra_gated_description: >-
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If you want to learn more about how we process your personal data, please read
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our <a href="https://mistral.ai/terms/">Privacy Policy</a>.
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---
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# Model Card for Mistral-7B-Instruct-v0.1
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## Encode and Decode with `mistral_common`
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```py
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from mistral_common.tokens.tokenizers.mistral import MistralTokenizer
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from mistral_common.protocol.instruct.messages import UserMessage
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from mistral_common.protocol.instruct.request import ChatCompletionRequest
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mistral_models_path = "MISTRAL_MODELS_PATH"
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tokenizer = MistralTokenizer.v1()
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completion_request = ChatCompletionRequest(messages=[UserMessage(content="Explain Machine Learning to me in a nutshell.")])
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tokens = tokenizer.encode_chat_completion(completion_request).tokens
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```
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## Inference with `mistral_inference`
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```py
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from mistral_inference.transformer import Transformer
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from mistral_inference.generate import generate
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model = Transformer.from_folder(mistral_models_path)
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out_tokens, _ = generate([tokens], model, max_tokens=64, temperature=0.0, eos_id=tokenizer.instruct_tokenizer.tokenizer.eos_id)
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result = tokenizer.decode(out_tokens[0])
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print(result)
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```
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## Inference with hugging face `transformers`
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```py
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from transformers import AutoModelForCausalLM
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model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1")
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model.to("cuda")
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generated_ids = model.generate(tokens, max_new_tokens=1000, do_sample=True)
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# decode with mistral tokenizer
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result = tokenizer.decode(generated_ids[0].tolist())
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print(result)
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```
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> [!TIP]
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> PRs to correct the `transformers` tokenizer so that it gives 1-to-1 the same results as the `mistral_common` reference implementation are very welcome!
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---
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The Mistral-7B-Instruct-v0.1 Large Language Model (LLM) is a instruct fine-tuned version of the [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) generative text model using a variety of publicly available conversation datasets.
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For full details of this model please read our [paper](https://arxiv.org/abs/2310.06825) and [release blog post](https://mistral.ai/news/announcing-mistral-7b/).
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## Instruction format
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In order to leverage instruction fine-tuning, your prompt should be surrounded by `[INST]` and `[/INST]` tokens. The very first instruction should begin with a begin of sentence id. The next instructions should not. The assistant generation will be ended by the end-of-sentence token id.
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E.g.
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```
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text = "<s>[INST] What is your favourite condiment? [/INST]"
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"Well, I'm quite partial to a good squeeze of fresh lemon juice. It adds just the right amount of zesty flavour to whatever I'm cooking up in the kitchen!</s> "
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"[INST] Do you have mayonnaise recipes? [/INST]"
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```
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This format is available as a [chat template](https://huggingface.co/docs/transformers/main/chat_templating) via the `apply_chat_template()` method:
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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device = "cuda" # the device to load the model onto
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model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1")
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tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1")
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messages = [
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{"role": "user", "content": "What is your favourite condiment?"},
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{"role": "assistant", "content": "Well, I'm quite partial to a good squeeze of fresh lemon juice. It adds just the right amount of zesty flavour to whatever I'm cooking up in the kitchen!"},
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{"role": "user", "content": "Do you have mayonnaise recipes?"}
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]
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encodeds = tokenizer.apply_chat_template(messages, return_tensors="pt")
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model_inputs = encodeds.to(device)
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model.to(device)
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generated_ids = model.generate(model_inputs, max_new_tokens=1000, do_sample=True)
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decoded = tokenizer.batch_decode(generated_ids)
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print(decoded[0])
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```
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## Model Architecture
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This instruction model is based on Mistral-7B-v0.1, a transformer model with the following architecture choices:
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- Grouped-Query Attention
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- Sliding-Window Attention
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- Byte-fallback BPE tokenizer
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## Troubleshooting
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- If you see the following error:
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```
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Traceback (most recent call last):
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File "", line 1, in
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File "/transformers/models/auto/auto_factory.py", line 482, in from_pretrained
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config, kwargs = AutoConfig.from_pretrained(
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File "/transformers/models/auto/configuration_auto.py", line 1022, in from_pretrained
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config_class = CONFIG_MAPPING[config_dict["model_type"]]
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File "/transformers/models/auto/configuration_auto.py", line 723, in getitem
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raise KeyError(key)
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KeyError: 'mistral'
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```
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Installing transformers from source should solve the issue
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pip install git+https://github.com/huggingface/transformers
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This should not be required after transformers-v4.33.4.
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## Limitations
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The Mistral 7B Instruct model is a quick demonstration that the base model can be easily fine-tuned to achieve compelling performance.
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It does not have any moderation mechanisms. We're looking forward to engaging with the community on ways to
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make the model finely respect guardrails, allowing for deployment in environments requiring moderated outputs.
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## The Mistral AI Team
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Albert Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lélio Renard Lavaud, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, William El Sayed.
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{
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"architectures": [
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"MistralForCausalLM"
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],
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 32768,
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"model_type": "mistral",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"rope_theta": 10000.0,
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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": "4.34.0.dev0",
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"use_cache": true,
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"vocab_size": 32000
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}
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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
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}
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||||
}
|
||||
3
pytorch_model-00001-of-00002.bin
Normal file
3
pytorch_model-00001-of-00002.bin
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
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||||
oid sha256:2f237251ac3ecb3bcbd8978b3eb7b55b5e83c06cd5224b276d2d8462773488c8
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size 9943028044
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3
pytorch_model-00002-of-00002.bin
Normal file
3
pytorch_model-00002-of-00002.bin
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
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||||
oid sha256:d9e54fbaabfe2c5d00d2a642398c5959c1eb31e9d9d40c80bd5d7c2c4067d3e1
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size 5064823659
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3
pytorch_model.bin.index.json
Normal file
3
pytorch_model.bin.index.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
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||||
oid sha256:f2d239108d89fb1568b9041e23f8526879c3fd500f65ac8d7c3204b270b648ef
|
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size 23950
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23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "</s>",
|
||||
"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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"unk_token": {
|
||||
"content": "<unk>",
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"lstrip": false,
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||||
"normalized": false,
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||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
91113
tokenizer.json
Normal file
91113
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
Binary file not shown.
BIN
tokenizer.model.v1
Normal file
BIN
tokenizer.model.v1
Normal file
Binary file not shown.
44
tokenizer_config.json
Normal file
44
tokenizer_config.json
Normal file
@@ -0,0 +1,44 @@
|
||||
{
|
||||
"add_bos_token": true,
|
||||
"add_eos_token": false,
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|
||||
"0": {
|
||||
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|
||||
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|
||||
"special": true
|
||||
},
|
||||
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|
||||
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||||
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||||
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|
||||
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||||
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"special": true
|
||||
},
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||||
"2": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [],
|
||||
"bos_token": "<s>",
|
||||
"chat_template": "{%- if messages[0]['role'] == 'system' %}\n {%- set system_message = messages[0]['content'] %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set loop_messages = messages %}\n{%- endif %}\n\n{{- bos_token }}\n{%- for message in loop_messages %}\n {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}\n {{- raise_exception('After the optional system message, conversation roles must alternate user/assistant/user/assistant/...') }}\n {%- endif %}\n {%- if message['role'] == 'user' %}\n {%- if loop.first and system_message is defined %}\n {{- ' [INST] ' + system_message + '\\n\\n' + message['content'] + ' [/INST]' }}\n {%- else %}\n {{- ' [INST] ' + message['content'] + ' [/INST]' }}\n {%- endif %}\n {%- elif message['role'] == 'assistant' %}\n {{- ' ' + message['content'] + eos_token}}\n {%- else %}\n {{- raise_exception('Only user and assistant roles are supported, with the exception of an initial optional system message!') }}\n {%- endif %}\n{%- endfor %}\n",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "</s>",
|
||||
"legacy": false,
|
||||
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|
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"pad_token": null,
|
||||
"sp_model_kwargs": {},
|
||||
"spaces_between_special_tokens": false,
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"unk_token": "<unk>",
|
||||
"use_default_system_prompt": false
|
||||
}
|
||||
Reference in New Issue
Block a user