Text Generation
Transformers
Safetensors
English
mixtral
mathematics
reasoning
algebra
arithmetic
geometry
calculus
statistics
number-theory
ai
adaption-labs
autoscientist
lora
education
stem
conversational
text-generation-inference
Instructions to use Charley890/AdaptiveMath with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Charley890/AdaptiveMath with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Charley890/AdaptiveMath") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Charley890/AdaptiveMath") model = AutoModelForCausalLM.from_pretrained("Charley890/AdaptiveMath", device_map="auto") 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 Settings
- vLLM
How to use Charley890/AdaptiveMath with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Charley890/AdaptiveMath" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Charley890/AdaptiveMath", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Charley890/AdaptiveMath
- SGLang
How to use Charley890/AdaptiveMath 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 "Charley890/AdaptiveMath" \ --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": "Charley890/AdaptiveMath", "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 "Charley890/AdaptiveMath" \ --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": "Charley890/AdaptiveMath", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Charley890/AdaptiveMath with Docker Model Runner:
docker model run hf.co/Charley890/AdaptiveMath
Upload 9 files
Browse files- README.md +200 -1
- adapter_config.json +36 -0
- adapter_model.safetensors +3 -0
- chat_template.jinja +24 -0
- config.json +36 -0
- special_tokens_map.json +6 -0
- tokenizer.json +0 -0
- tokenizer_config.json +19 -0
- trainer_state.json +746 -0
README.md
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| 1 |
---
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base_model: mistralai/Mixtral-8x7B-Instruct-v0.1
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library_name: peft
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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### Framework versions
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- PEFT 0.15.1
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adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "mistralai/Mixtral-8x7B-Instruct-v0.1",
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"bias": "none",
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"corda_config": null,
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"eva_config": null,
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"exclude_modules": [],
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 128,
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"lora_bias": false,
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"lora_dropout": 0.0,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 64,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"o_proj",
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"q_proj",
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"k_proj",
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"v_proj"
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],
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"task_type": "CAUSAL_LM",
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"trainable_token_indices": null,
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"use_dora": false,
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"use_rslora": false
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}
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:7fc2b429bf7dd277d8baadbdbd24755c8589934c559337d65ab72b83048ce621
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size 218138576
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chat_template.jinja
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{%- if messages[0]['role'] == 'system' %}
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{%- set system_message = messages[0]['content'] %}
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{%- set loop_messages = messages[1:] %}
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{%- else %}
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| 5 |
+
{%- set loop_messages = messages %}
|
| 6 |
+
{%- endif %}
|
| 7 |
+
|
| 8 |
+
{{- bos_token }}
|
| 9 |
+
{%- for message in loop_messages %}
|
| 10 |
+
{%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}
|
| 11 |
+
{{- raise_exception('After the optional system message, conversation roles must alternate user/assistant/user/assistant/...') }}
|
| 12 |
+
{%- endif %}
|
| 13 |
+
{%- if message['role'] == 'user' %}
|
| 14 |
+
{%- if loop.first and system_message is defined %}
|
| 15 |
+
{{- ' [INST] ' + system_message + '\n\n' + message['content'] + ' [/INST]' }}
|
| 16 |
+
{%- else %}
|
| 17 |
+
{{- ' [INST] ' + message['content'] + ' [/INST]' }}
|
| 18 |
+
{%- endif %}
|
| 19 |
+
{%- elif message['role'] == 'assistant' %}
|
| 20 |
+
{{- ' ' + message['content'] + eos_token}}
|
| 21 |
+
{%- else %}
|
| 22 |
+
{{- raise_exception('Only user and assistant roles are supported, with the exception of an initial optional system message!') }}
|
| 23 |
+
{%- endif %}
|
| 24 |
+
{%- endfor %}
|
config.json
ADDED
|
@@ -0,0 +1,36 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"MixtralForCausalLM"
|
| 4 |
+
],
|
| 5 |
+
"attention_dropout": 0.0,
|
| 6 |
+
"bos_token_id": 1,
|
| 7 |
+
"dtype": "bfloat16",
|
| 8 |
+
"eos_token_id": 2,
|
| 9 |
+
"head_dim": null,
|
| 10 |
+
"hidden_act": "silu",
|
| 11 |
+
"hidden_size": 4096,
|
| 12 |
+
"initializer_range": 0.02,
|
| 13 |
+
"intermediate_size": 14336,
|
| 14 |
+
"max_position_embeddings": 32768,
|
| 15 |
+
"model_type": "mixtral",
|
| 16 |
+
"num_attention_heads": 32,
|
| 17 |
+
"num_experts_per_tok": 2,
|
| 18 |
+
"num_hidden_layers": 32,
|
| 19 |
+
"num_key_value_heads": 8,
|
| 20 |
+
"num_local_experts": 8,
|
| 21 |
+
"output_router_logits": false,
|
| 22 |
+
"pad_token_id": 2,
|
| 23 |
+
"rms_norm_eps": 1e-05,
|
| 24 |
+
"rope_parameters": {
|
| 25 |
+
"rope_theta": 1000000.0,
|
| 26 |
+
"rope_type": "default"
|
| 27 |
+
},
|
| 28 |
+
"router_aux_loss_coef": 0.02,
|
| 29 |
+
"router_jitter_noise": 0.0,
|
| 30 |
+
"sliding_window": null,
|
| 31 |
+
"tie_word_embeddings": false,
|
| 32 |
+
"transformers_version": "5.10.1",
|
| 33 |
+
"use_cache": false,
|
| 34 |
+
"vocab_size": 32000,
|
| 35 |
+
"torch_dtype": "bfloat16"
|
| 36 |
+
}
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token": "<s>",
|
| 3 |
+
"eos_token": "</s>",
|
| 4 |
+
"pad_token": "</s>",
|
| 5 |
+
"unk_token": "<unk>"
|
| 6 |
+
}
|
tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,19 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": null,
|
| 3 |
+
"additional_special_tokens": [],
|
| 4 |
+
"backend": "tokenizers",
|
| 5 |
+
"bos_token": "<s>",
|
| 6 |
+
"clean_up_tokenization_spaces": false,
|
| 7 |
+
"eos_token": "</s>",
|
| 8 |
+
"is_local": false,
|
| 9 |
+
"legacy": false,
|
| 10 |
+
"local_files_only": true,
|
| 11 |
+
"model_max_length": 32768,
|
| 12 |
+
"pad_token": "</s>",
|
| 13 |
+
"padding_side": "right",
|
| 14 |
+
"sp_model_kwargs": {},
|
| 15 |
+
"spaces_between_special_tokens": false,
|
| 16 |
+
"tokenizer_class": "TokenizersBackend",
|
| 17 |
+
"unk_token": "<unk>",
|
| 18 |
+
"use_default_system_prompt": false
|
| 19 |
+
}
|
trainer_state.json
ADDED
|
@@ -0,0 +1,746 @@
|
|
|
|
|
|
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|
|
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|
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